IHhSIS MICHIGAN STATE UNIVERSITY LIBRARIES II IIII I IIIIIIII IIII 3 1293 10637 1374 III III L This is to certify that the dissertation entitled / AN IN—DEPTH STUDY OF THE AMOUNT OF USE OF TEACHER LEAVE TIME IN THE DAVISON COMMUNITY SCHOOLS presented by Robert C. Amble has been accepted towards fulfillment of the requirements for Ph.D . degree in Educational Administrat ion Major professor Date % ' L’ MSUi'rnnAffinnmim. A ' F ' ' 1 m .- 0-12771 , III-€31" EEERQ ‘ , at: News 1%?th Umfiemfi MSU mg... -4_» :3. I? 32? RETURNING MATERIALS: P ace in book rop to remove this checkout from LIBRARIES _ 4...:3..-._ your record. FINES W111 be charged if book is returned after the date stamped below. 4' >21 ”1 I V '2 awe-rim 930/ 4 W0 AN IN-DEPTH STUDY OF THE AMOUNT OF USE OF TEACHER LEAVE TIME IN THE DAVISON COMMUNITY SCHOOLS By Robert C. AmbIe A DISSERTATION Submitted to Michigan State University in partial fquiIIment of the requirements for the degree of DOCTOR OF PHILOSOPHY Department of Administration and Higher Education 1982 Ing I six-j was I cite Febr Ions higI Hen IIII Dav Int ABSTRACT AN IN-DEPTH STUDY OF THE AMOUNT OF USE OF TEACHER LEAVE TIME IN THE DAVISON COMMUNITY SCHOOLS By Robert C. AmbTe One purpose of the study was to secure accurate information regard— ing the amount of Teave time that Davison teachers have used over a six—year period, 1974-75 to 1978—79 and 1980-81. Statisticai information was compiied on teacher Teave time used within the above time frame. ResuIts of the study showed that Davison teachers were absent most often on Monday, foTTowed by Tuesday, Friday, Thursday, and Wednesday. The rate of absenteeism was highest during March, succeeded by February, December, and May. The percentage of absenteeism was aTways lowest in September. The percentage of absenteeism was higher for eTementary and junior high schooI teachers than for high schooI staff, and younger teachers were absent more often than oIder teachers. Other findings are contained in Chapters IV and V of the study. The second purpose of the study was to use an experimenta] design in order to attempt to bring about a change in behavior on the part of Davison teachers regarding usage of Ieave benefits. The roIe of the researcher in this study was to gather information and statistics regarding the usage of Teave time by Davison teachers, as well as what re substitute teac principals, the teachers. It on sponsor the ide to use Ieave ti opportunity to by building grt The foIIowing p ResuIts . genera], remap the category ..‘ staff was c] as Staff membErs Robert C. AmbTe weTI as what research has shown about the educationai ineffectiveness of substitute teachers. This information was then shared with the buiIding principaIs, the Davison Education Association Teadership, and the teachers. It was hoped that the Davison teaching staff woqu then sponsor the idea that ”something needs to be done” to encourage teachers to use Ieave time on a more judicious basis. The researcher then had an opportunity to observe whether or not the teaching staff as a whoTe and by budeing groups sponsored the idea that "something needs to be done". The foTTowing possibie behaviorai responses were present in each case: I. Sponsorship . Approva], but not sponsorship . NeutraIity th . Inactive opposition 5. Active opposition ResuIts of the study indicated that the Davison teaching staff, in general, remained neutraT. The SipTe EIementary SchooT staff feTT into the category "approvaT, but not sponsorship". The junior high schooI staff was cIassified under "inactiVe opposition". The professionaT staff members of the other six buiIdings were cTassified as "neutraI". Special 1 Johnson, and Dr coulnittee, for Dr. Chris Sooner his willingness that these men counselors. I owe muc assistance and this study and Finally, my wife Barbar; Support and em Writing this (1‘ ACKNOWLEDGMENTS Special thanks should go to the late Dr. Archibald Shaw, Dr. Van Johnson, and Dr. Richard Featherstone who served as chairman of my committee, for their suggestions and encouragement. My appreciation to Dr. Chris Sower for his helpful suggestions and to Dr. Glen Cooper for his willingness to serve on my guidance committee. I feel very fortunate that these men have truly been my friends as well as my advisors and counselors. I owe much appreciation.to Barbara Kaza and Joyce Maehre for their assistance and encouragement during the various stages of conducting this study and the writing of this dissertation. Finally, my most sincere expression of gratitude is extended to my wife Barbara, daughter Karen, and sons Robert Jr. and Jon for their Support and encouragement through the years of academic study and in writing this dissertation. ii CHAPTER I. THE PRC Stat The Thec Defi Limi Orga II. REVIEH Hist How Hone Inst Pub'. Comp Stre Tear P0pp Natl Ana‘ TES‘ Otm Nul' Sum TABLE OF CONTENTS CHAPTER Page I. THE PROBLEM ............................................. 1 Statement of the Problem ............................. l The Purpose .......................................... 2 Theory ............................................... 4 Definition of Terms .................................. 6 Limitations of the Study ............................. 8 Organization of the Study ............................ 8 II. REVIEW OF THE LITERATURE ................................ 9 Historical Information ............................... 9 How Widespread is the Problem? ....................... ll Monetary Cost of Absenteeism ......................... ll Instructional Costs of Teacher Absenteeism ........... l3 Public Perception of Teacher Absenteeism ............. l5 Comparison of Student and Teacher Attendance Patterns l6 Stress and Teacher Absenteeism ....................... l7 Major Causes of Employee Absenteeism ................. l8 Research Findings .................................... 19 Need for Further Research ............................ 24 Summary .............................................. 24 III. DESIGN OF THE STUDY ..................................... 26 Theory of Involvement or Change ...................... 26 Superintendent's Role ................................ 26 Principal's Role ..................................... 27 Association's Role ................................... 28 Teacher's Role ....................................... 28 Methodology .......................................... 29 Population Studied ................................... 30 Nature of the Data ................................... 3l Analysis Procedures .................................. 32 Tests for Treatment Effect and for Absenteeism ....... 33 Other Research Considerations ........................ 34 Null Hypotheses ...................................... 35 Summary .............................................. 36 iii CHAPTER III. ANALYS Exp Tre Ies Res Tes PEI Sur PIER V. ANALYSIS OF THE RESULTS ................................. Experimental Design .................................. Davison Education Association Executive Board ..... Central Elementary Staff .......................... Gates Elementary Staff ............................ Hill-Uptegraff Staff .............................. Siple Elementary School Staff ..................... Thomson Elementary Staff .......................... Wolcott Elementary Staff .......................... Junior High School Staff .......................... Senior High School Staff .......................... Staff Overview .................................... Treatment ............................................ Tests for Treatment Effects .......................... Results of the Tests for Treatment Effects ........... Days of the Week, Tests for Treatment Effect ...... Days of the Week, Modified Treatment Effects ...... Days of the Week, Test for Interaction Between Age and Treatment .............................. Months of the Year, Tests for Treatment Effect.... Months of the Year, Modified Treatment Effects.... Months of the Year, Test for Interaction Between Age and Treatment .............................. Reasons for Absence, Tests for Treatment Effect... Reasons for Absence, Modified Treatment Effects... Reasons for Absence, Tests for Interaction Between Age and Treatment .............................. Tests for Absenteeism ................................ Days of the Week .................................. Test for Relationship Between Age and Average Absenteeism by Days of the Week ................ Tests for Effects of Sex, Level, and District on Average Absenteeism by Months of the Year ...... Tests for Relationship Between Age and Average Absenteeism by Months of the Year .............. Tests for Effects of Sex, Level, and District on Average Absenteeism by Reasons for Absence ..... Tests for Relationship Between Age and Average Absenteeism by Reasons for Absence ............. Percentage of Absence--General Statistics ............ Age Group--Six—Year Totals ........................ Illness-—Six-Year Totals by Level ................. Days of the Week—-Six-Year Totals ................. Months of the Year--Six—Year Totals ............... Percentage of Absenteeism by Year--Six-Year Totals Summary .............................................. Page TT7 T33 T33 T59 T59 T74 T78 T78 T85 T85 T89 T89 CHAPTER BIBLIOGRAPHY. APPENDICES A. A FINA 8. ST 'TIS ER Page SUMMARY, CONCLUSIONS, DISCUSSION, AND IMPLICATIONS FOR FURTHER RESEARCH ..................................... l92 Summary .............................................. 192 Conclusions .......................................... 2T0 Discussion ........................................... 2T3 Implications for Future Research ..................... 2T7 OGRAPHY ................................................... 2l9 DICES A FINAL LOOK AT THE THEORY .............................. 222 STATISTICAL INFORMATION——l974-75 THROUGH 1978-79 ........ 226 v TABLE II. A Rese Staff Member 4.2. Test 1 F-TESI 4.3. Test I F-lesi 4-4. lest‘ F-Tes’ 4~5. lest ‘ F-TES‘ 4.6. Test . F-TES‘ h7- Test‘ I8° Perce Level 4‘9' Sunna Broke 4~I0. TeSt ~ Test ' ' Test ' Perce Level ' SUmma Broke LIST OF TABLES Page A Research Guide for Observing the Involvement of School Staff in Sponsoring a Change in the Attitude of Staff I Members Towards the Use of Leave Time ................... 40 Test for Treatment Effect for Mondays, Univariate F-Tests with (l.90) D. F ................................ 49 Test for Treatment Effect for Tuesdays, Univariate F-Tests with (l.90) D. F ................................ 49 Test for Treatment Effect for Wednesdays, Univariate F-Tests with (l.90) D. F ................................ 50 Test for Treatment Effect for Thursdays, Univariate F-Tests with (l.90) D. F ................................ 50 Test for Treatment Effect for Fridays, Univariate F—Tests with (l.90) D. F ................................ 5T Test for Modified Treatment Effects on Mondays .......... 52 Percentage of Absence for Mondays When Broken Down by Level by Years .......................................... 54 Summaries of Means by Year for Staff Absence When Broken Down by Level by Mondays ......................... 55 Test for Modified Treatment Effects on Tuesdays ......... 57 Test for Modified Treatment Effects on Wednesdays ....... 57 Test for Modified Treatment Effects on Thursdays ........ 58 Percentage of Absence for Thursdays When Broken Down by Level by Years .......................................... 59 Summaries of Means by Year for Staff Absence When Broken Down by Level by Thursdays ....................... 61 vi TABLE 4.l5. 4T6. 4.17. 4.18. 4J9. 420. 42L 422. 423. 424. 425. 426. 427. 4.28. 424 4-30. Test f Test f Monday Test f Tuesda Test f Hednes Test f Thursd Test f Friday Test f F-lest Test f F-Test Test f F-Test Test f F-Test Test f F~Test Test f F-Test Test f F~Test Test f F~Test Test f F~Test lest f F~Test Test for Modified Treatment Effects on Fridays .......... Test for Interaction Between Age and Treatment for Mondays. Univariate F—Tests with (1.90) D. F ........... Test for Interaction Between Age and Treatment for Tuesdays. Univariate F-Tests with (l.90) D. F .......... Test for Interaction Between Age and Treatment for Wednesdays. Univariate F-Tests with (l.90) D. F ........ Test for Interaction Between Age and Treatment for Thursdays. Univariate F-Tests with (1.90) D. F ......... Test for Interaction Between Age and Treatment for Fridays. Univariate F-Tests with (l.90) D. F ........... Test for Treatment Effect for September. Univariate F-Tests with (l.90) D. F ................................ Test for Treatment Effect for October. Univariate F— Tests with (l. 90)D F ................................ Test for Treatment Effect for November. Univariate F—Tests with (l.90) D. F ................................ Test for Treatment Effect for December. Univariate F-Tests with (1.90) D. F ................................ Test for Treatment Effect for January. Univariate F—Tests with (l.90) D. F ................................ Test for Treatment Effect for February. Univariate F-Tests with (1.90) D. F ............................... Test for Treatment Effect for March. Univariate F-Tests with (1.90) D. F ............................... Test for Treatment Effect for April. Univariate F-Tests with (l.90) D. F ............................... Test for Treatment Effect for May. Univariate F-Tests with (l.90) D. F ............................... Test for Treatment Effect for June. Univariate F-Tests with (1.90) D. F ............................... vii Page 62 64 64 65 65 66 68 68 69 69 7O 72 72 73 73 74 TABLE 43l. Test‘ 4.32. Percei 4.33. lest ‘ 434. Test‘ 4.35. lest ‘ 436. Test' 437. Test 438. lest‘ 4.39. Percel Distr 4.40. Test . 4.4T. Perce: 4.42. gm by Le 4-43. Test. 445. Test . sePta T4P- Test- Octob T47. Test NOVem T48. Test Decem 449- TeSt Janua {50' Perce tee a Test for Modified Treatment Effects for September ....... Percentage of Absence for September Broken Down by Sex.. Test for Modified Treatment Effects for October ......... Test for Modified Treatment Effects for November ........ Test for Modified Treatment Effects for December ........ Test for Modified Treatment Effects for January ......... Test for Modified Treatment Effects for February ........ Test for Modified Treatment Effects for March ........... Percentage of Absence for March When Broken Down by District ................................................ Test for Modified Treatment Effects for April ........... Percentage of Absence in April When Broken Down by Level Summaries of Means for Absence in April When Broken Down by Level and Year ....................................... Test for Modified Treatment Effects for May ............. Test for Modified Treatment Effects for June ............ Test for Interaction Between Age and Treatment for September. Univariate F-Tests with (l.90) D. F ......... Test for Interaction Between Age and Treatment for October. Univariate F-Tests with (l.90) D. F ........... Test for Interaction Between Age and Treatment for November. Univariate F-Tests with (l.90) D. F .......... Test for Interaction Between Age and Treatment for December. Univariate F-Tests with (l.90) D. F .......... Test for Interaction Between Age and Treatment for January. Univariate F-Tests with (l.90) D. F ........... Percentage of Absence for January When Broken Down by Age Groups .............................................. viii Page 75 76 78 78 79 8T 81 82 83 85 86 87 89 89 90 90 92 92 93 94 TABLE 454 45. N 45. (A) 45 . .> 45. ()1 4.5. O‘- 4.5. \5 458. 459. 460. 464 462. 463. 4.64. 465. Sunnaries Age Group Test for February Test for March. Test for April. Test in May. U Test to Univari Test to Univari Test fr Univar Test f Busine Test f Univar Test 1 Leave. Test tion (1.90 Test Univa lest Illnc Test PErsi Summaries of Absence for January When Broken Down by Age Groups .............................................. Test for Interaction Between Age and Treatment for February. Univariate F-Tests with (l.90) D. F .......... Test for Interaction Between Age and Treatment for March. Univariate F-Tests with (l.90) D. F ............. Test for Interaction Between Age and Treatment for April. Univariate F-Tests with (l.90) D. F ............. Test for Interaction Between Age and Treatment for May. Univariate F—Tests with (l.90) D. F ............... Test for Interaction Between Age and Treatment for June. Univariate F-Tests with (1.90) D. F ..................... Test for Treatment Effect on Absence for Illness. Univariate F-Tests with (l.90) D. F ..................... Test for Treatment Effect on Absence for Personal Leave. Univariate F—Tests with (l.90) D. F ..................... Test for Treatment Effect on Absence for School Business. Univariate F-Tests with (l.90) D. F .......... Test for Treatment Effect on Absence for Dock Days. Univariate F-Tests with (l.90) D. F ..................... I Test for Treatment Effect on Absence for Bereavement Leave. Univariate F-Tests with (l.90) D. F ............. Test for Treatment Effect on Absence for Davison Educa— tion Association Business. Univeriate F—Tests with (l.90) D. F ............................................. Test for Treatment Effect on Absence for Jury Duty. Univariate F-Tests with (1.90) D. F ..................... Test for Modified Treatment Effects on Absence for Illness ................................................. Test for Modified Treatment Effects on Absence for Personal Leave .......................................... Page 95 97 97 98 98 99 TOT TOT T02 T02 T03 T05 T05 T06 T06 TABLE 466. 467. 468. \O 4.6. 478. 472. 473. 4.74. 475. 476. 477. 4.78. Test in School Test fc Days... Test it Bereave Test it Davison Percent Down b1 . . lest f Duty.. Test f Absenc D. F.. Test f Absent (l.90) Test f Absenc (1.90) Test f Absenc D. F.. Test 1 Absenc (1.901 Test I Absenr Univa Test for Modified Treatment Effects on Absence for School Business ......................................... Test for Modified Treatment effects on Absence for Dock Days .................................................... Test for Modified Treatment Effects on Absence for Bereavement Leave ....................................... Test for Modified Treatment Effects on Absence for Davison Education Association Business .................. Percentage of Absence for D. E. A. Business When Broken Down by Sex ............................................. Test for Modified Treatment Effects on Absence for Jury Duty .................................................... Test for Interaction Between Age and Treatment for Staff Absence for Illness. _Univariate F-Tests with (l.90) D. F .................................................... Test for Interaction Between Age and Treatment for Staff Absence for Personal Leave. Univariate F—Tests with (1.90) D. F ............................................. Test for Interaction Between Age and Treatment for Staff Absence for School Business. Univariate F-Tests with (1.90) D. F ............................................. Test for Interaction Between Age and Treatment for Staff Absence for Dock Days. Univariate F—Tests with (1.90) D. F .................................................... Test for Interaction Between Age and Treatment for Staff Absence for Bereavement Leave. Univariate F-Tests with (l.90) D. F ............................................. Test for Interaction Between Age and Treatment for Staff Absence for Davison Education Association Business. Univariate F-Tests with (l.90) D. F ..................... Test for Interaction Between Age and Treatment for Staff Absence for Jury Duty. Univariate F-Tests with (l.90) D. F .................................................... Page 108 108 109 T09 110 112 114 114 115 115 116 118 1 TABLE 4.19. 4.81. 4.82. 485. 4.86. 487. 489. 4.90. 491. 492. 493. 4.94 Test f Absent . Percen and by Absent Mean T Distri . Test t Absent . Percer and by Absent Mean‘ Distr Test‘ Absen - Test Absen Perce Sex a Means Mean Distr Test Abser Page Test for Effects of Sex, Level, and District on Average Absenteeism on Mondays .................................. 119 Percentage of Absenteeism on Mondays Broken Down by Sex and by District of Residence ............................ 120 Absenteeism on Mondays by Sex and District .............. 121 Mean Total Percentage of Absenteeism by Sex and by District for Mondays .................................... 122 Test for Effects of Sex, Level, and District on Average Absenteeism on Tuesdays ................................. 124 Percentage of Absenteeism on Tuesdays Broken Down by Sex and by District of Residence ............................ 125 Absenteeism on Tuesdays by Sex and District ............. 126 Mean Total Percentage of Absenteeism by Sex and By District for Tuesdays ................................... 127 Test for Effects of Sex, Level, and District on Average Absenteeism on Wednesdays ............................... 129 Test for Effects of Sex, Level, and District on Average Absenteeism on Thursdays ................................ 129 Percentage of Absenteeism on Thursdays Broken Down by Sex and by District of Residence ........................ 130 Means of Absenteeism on Thursdays by Sex and By District 131 Mean Total Percentage of Absenteeism by Sex and by District for Thursdays .................................. 132 Test for Effects of Sex, Level, and District on Average Absenteeism on Fridays .................................. 134 Test for the Relationship Between Age and Average Absenteeism on Mondays. Regression Analysis for Within Cells Error Term. Dependent Variable--Average .......... 135 Test for the Relationship Between Age and Average Absenteeism on Tuesdays. Regression Analysis for Within Cells Error Term. Dependent Variable-~Average .......... 135 xi TABLE 495. Test Abser Hith' 496. Test Abse: with“ 497 Test Abse‘ Kitt' 498 Test Abse 499. 2erc L948 1100. Mean Dist Abse 4102 Test Abse 4103~ Test Abse 4104- Test Abse 4105, Eerc and 4.106. Near 4'107' Hear Dist 4108~ Test Bbse 4109_ Peri and Test for the Relationship Between Age and Average Absenteeism on Wednesdays. Regression Analysis for Within Cells Error Term. Dependent Variable—-Average... Test for the Relationship Between Age and Average Absenteeism on Thursdays. Regression Analysis for Within Cells Error Term. Dependent Variable--Average... Test for the Relationship Between Age and Average Absenteeism on Fridays. Regression Analysis for Within Cells Error Term. Dependent Variable--Average... Test for Effects of Sex, Level, and District on Average Absenteeism in September ................................ Percentage of Absence in September When Broken Down by Level and by District by Year ........................... Mean Percentage of Absence in September by Level and District ................................................ Test for Effects of Sex, Level, and District on Average Absenteeism in October .................................. Test for Effects of Sex, Level, and District on Average Absenteeism in November ................................. Test for Effects of Sex, Level, and District on Average Absenteeism in December ................................. Test for Effects of Sex, Level, and District on Average Absenteeism in January .................................. Percentage of Absenteeism in Januarys Broken Down by Sex and District of Residence ............................... Means of Absenteeism in Januarys by Sex and District.... Mean Total Percentage of Absenteeism by Sex and by District for January .................................... Test for Effects of Sex, Level, and District on Average Absenteeism in February ................................. Percentage of Absenteeism in February Broken Down by Sex and District of Residence ............................... xii Page 135 136 136 137 138 139 141 141 142 142 143 144 145 147 148 4113. 4114. 4.121. 4.122. 4.123. 4.124. . Means . Mean Distr . Test Abser Perce and t by Le . Test Abser . Test Abser . Percr andl . Mean . Test Abse - Test Abse Hith Test Cell Test Abse With Test Abse Cell Test ADSe Cell Page 110. Means of Absenteeism in Februarys by Sex and District... 149 111 Mean Total Percentage of Absenteeism by Sex and by District for February ................................... 150 112 Test for Effects of Sex, Level, and District on Average Absenteeism in March .................................... 152 113 Percentage of Absenteeism in March Broken Down by Years and by Level ............................................ 14. Summaries of Means of Absence for March When Broken Down by Level ................................................ 154 15 Test for Effects of Sex, Level, and District on Average Absenteeism in April .................................... 156 16. Test for Effects of Sex, Level, and District on Average Absenteeism in May ...................................... 156 Percentage of Absence in May When Broken Down by Level and by District by Year ................................. 157 18. Mean Percentage of Absence in May by Level and District 158 19. Test for Effects of Sex, Level, and District on Average Absenteeism in June ..................................... 160 0. Test for the Relationship Between Age and Average Regression Analysis for 161 Absenteeism in September. Within Cells Error Term. Dependent Variable—-Average.. Test for the Relationship Between Age and Avera e Regression Analysis for Within 161 Absenteeism in October. Cells Error Term. Dependent Variable——Average ......... Test for the Relationship Between Age and Average Absenteeism in November. Regression Analysis for Within Cells Error Term. Dependent Variable——Average.. 161 Test for the Relationship Between Age and Avera e Regression Analysis for Within 162 Absenteeism in December. Cells Error Term. Dependent Variable--Average .......... Test for the Relationship Between Age and Average Absenteeism in January. Regression Analysis for Within Cells Error Term. Dependent Variable--Average ......... 162 xiii TABLE 4.125. ' 4.126. Abse - Test Abse ' Perc Dowr the' - Tes1 Abse Page Test for the Relationship Between Age and Average Absenteeism in February. Regression Analysis for Within Cells Error Term. Dependent Variable--Average.. 162 Test for the Relationship Between Age and Average Absenteeism in March. Regression Analysis for Within Cells Error Term. Dependent Variable-~Average ......... 163 Test for the Relationship Between Age and Average Absenteeism in April. Regression Analysis for Within Cells Error Term. Dependent Variable--Average ......... 163 Test for the Relationship Between Age and Average Absenteeism in May. Regression Analysis for Within Cells Error Term. Dependent Variable-—Average ......... 163 Test for the Relationship Between Age and Average Absenteeism in June. Regression Analysis for Within Cells Error Term. Dependent Variable--Average ......... 163 Test for Effect of Sex, Level, and District on Average Absenteeism for Illness ................................ 164 Percentage of Absenteeism for Illness When Broken Down by Sex and District of Residence ....................... 166 25. 7. Means of Absenteeism for Illness by Sex and District... 167 Iv Mean Total Percentage of Absenteeism by Sex and District for Illness ................................... 168 Test for Effects of Sex, Level, and District on Average Absenteeism for Personal Leave ......................... 169 Test for Effects of Sex, Level, and District on Average Absenteeism for School Business ........................ 171 Percentage of Absence for School Business When Broken Down by Years and by Level ............................. 172 Summaries of Means of Absence for School Business for the Six Years of the Study When Broken Down by Level... 173 Test for Effects of Sex, Level, and District on Average Absenteeism for Dock Days .............................. 175 TABLE 4.139. 4.140. 4.141. 4.142. 4.143. 4144. 4.145. 4.146. 4.147. 4.148. 4-149. 4450. Page ABLE Test for Effects of Sex, Level, and District on 175 .139. Average Absenteeism for Bereavement .................... Percentage of Absence for Bereavement Broken Down by Sex .................................................... 176 .141. Test for the Effects of Sex, Level, and District on Average Absenteeism for Davison Education Association 177 Business ............................................... Test for Effects of Sex, Level, and District on Average Absenteeism for Jury Duty .............................. 177 .140. .142. Test for the Relationship Between Age and Average Absenteeism for Illness. Regression Analysis for Within Cells Error Term. Dependent Variable--Average.. 179 .143. Test for the Relationship Between Age and Average Absenteeism for Personal Leave. Regression Analysis for Within Cells Error Term. Dependent Variable—- Average ................................................ Test for the Relationship Between Age and Average Absenteeism for School Business. Regression Analysis for Within Cells Error Term. Dependent Variable-- Average ................................................ Test for the Relationship Between Age and Average Absenteeism for Dock Days. Regression Analysis for Within Cells Error Term. Dependent Variable—-Average.. 180 144. 179 179 Test for the Relationship Between Age and Average Absenteeism for Bereavement. Regression Analysis for Within Cells Error Term. Dependent Variable--Average.. 180 Test for the Relationship Between Age and Average Absenteeism for Davison Education Association Business. Regression Analysis for Within Cells Error Term. Dependent VariabIe-—Average ............................ 180 47. 1. Test for the Relationship Between Age and Average Absenteeism for Jury Duty. Regression Analysis for Within Cells Error Term. Dependent Variable-—Average.. 181 Percentage of Absence When Broken Down by Age Group-— 182 Six—Year Totals ........................................ XV TABLE 4.151. 4.152. 4.153. 4154 Perct Yeah Snow by Lt Peru Peru 96 S‘ . Perc 3571 . Perc Perc Dist 1980 Mean Dist 'ABLE .151. .152. 153. 154. 155. 156. Percentage of Absence for Illness When Broken Down by Years and by Level-—Six-Year Totals .................... Summary of Means by Year for Illness When Broken Down by Level--Six-Year Totals .............................. Percentage of Absenteeism by Days of the Week .......... Percentage of Absenteeism by Months of the Year for 96 Staff Members ....................................... Percentage of Absenteeism by Months of the Year for 357 Staff Members ...................................... Percentage of Absenteeism by Year-~Six-Year Totals ..... Percentage of Absenteeism Broken Down by Sex and District of Residence for 1974-75 to 1978-79 and for 1980-81 ................................................ Means of Percentage of Absenteeism by Age and by District of Residence--Six-Year Totals ................. xvi Page 183 184 186 187 188 190 203 203 Itheneve Problem educa substitute te a regular cla negative impa Another Teacher absen 0T substitute reduced the n Education ove degrees in ed with the schc PT economic , 10" cPIIIIIETisat IVITIable Doc Sick Is an THIGdiate have been Wm CHAPTER I THE PROBLEM Statement of the Problem Whenever a teacher is absent from the classroom, it presents a )blem educationally for our school district. Research shows that Istitute teachers, in general, are not as effective educationally as negular classroom teacher. Teacher absence from the classroom has a ‘ative impact on our entire community. Another problem for our school district as a direct result of cher absence is the difficulty today of securing sufficient numbers substitute teachers. Institutions of higher learning have greatly Jced the number of graduates being granted degrees in the field of :ation over the past several years. University graduates with bees in education who were unable to secure full-time employment I the schools have sought and taken employment in other fields out conomic necessity. These two factors, combined with the relatively compensation of substitute teachers, have drastically reduced the lable pool of substitute teachers. Sick leave benefits were established to be used when a teacher or imediate member of the teacher's family was ill. Individuals who been working in the field of education for the past twenty-five to thirty years cal teachers. Some tional Ifringe access to perso time. This res certain sub-grt from other sub- that they are I The purp One pur; 119 the amoun‘ period (1974- information in Various reasc anaII’Z‘ed for sex; whether Of the distr Iunior high and TUTI~tin PT the Year tl"Inflated i 98 well as . the CIdSsif for the tot irty years can recall when there were no sick leave benefits for chers. Some teachers perceive sick leave benefits today as an addi- nal ”fringe benefit" to be ”used up” each year. Teachers also have ess to personal business days, school business days, and bereavement e. This research study is being conducted to determine whether tain sub-groups within the Davison teaching staff vary significantly m other sub-groups, or from the total faculty, in the amount of time t they are out of the classroom for the reasons given above. The Purpose The purpose of this study was two-fold. One purpose of the study was to secure accurate information regard- the amount of leave time Davison teachers have used over a five-year iod (1974-75, 1975-76, 1976-77, 1977-78, and 1978-79). Statistical armation was gathered and compiled on teacher leave time used for ious reasons over that period of time. This information was then yzed for each teacher according to the following categories: age; whether they reside inside the school district boundaries or outside he district; grade-level and subject-area assignment; elementary, or high school, or senior high school teaching assignment; part-time full-time teachers; days of the week that leave was used; and months he year that leave was used. This information was compiled and slated into total dollar expenditures and per teacher expenditures, ell as total leave days used and days used per teacher according to classifications outlined above. This same information was summarized he total five-year period. The secor in order to att Davison teacher the statistica‘ fessional staf and the Daviso rejection. Th methods. The firs Davison Educat the D. E. A. l governing bed to show the e given an oppo been Presente the idea that Title time or antTCIPati on D' E- II. strr The otI VISIT to an SEDtation ma cTassroorn te H the Staff BWI The PIGSent 111 t The second purpose of this study was to use an experimental design n order to attempt to bring about a change in behavior on the part of avison teachers regarding teacher usage of leave benefits. A summary of he statistical infbrmation described above was introduced to the pro- ssional staff. An observation was then made as to whether the staff d the Davison Education Association responded with sponsorship or jection. This information was introduced to the teaching staff by two The first method used was to make the information available to the avison Education Association. This was accomplished by a meeting with re D. E. A. Executive Board on Tuesday, September 9, 1980. This is the rverning body of the local teacher union. A presentation was introduced ~ show the extent of the problem. The members of the board were then ven an opportunity to ask questions regarding the information that had en presented. It was hoped that the D. E. A. hierarchy would sponsor e idea that ”something needs to be done" to encourage teachers to use ave time on a more judicious basis. The information was presented in ticipation that there would be official action through the formal E. A. structure to this end. The other approach to teachers that was employed was a personal sit to each of the school buildings by the superintendent, with a pre- rtation made at building staff meetings. The importance of the regular .ssroom teacher to the student learning process was emphasized in each the staff meetings as well as the meeting with the D. E. A. Executive rd. The opportunity to observe the following behavioral responses was sent in each case: A, Spons 8. Apart C. Meutr D. Inact E. Actir Researc are many caus Banter found someone other One pri “teacher burr I‘OUIID ,” say Counseling at be caused by are three 191 T09419449, WDI‘I bUTIasts tw: ASUIcers, c Increa A. Sponsorship B. Approval, but not sponsorship C. Neutrality D. Inactive opposition E. Active opposition Theory Research in the field of teacher absenteeism indicates that there many causes for teachers being out of their classrooms. Chrissie ber found that on any one day, 86,000 classrooms are covered by 1 one other than the regular teacher. One primary cause for absenteeism among teachers is what is called acher burnout”. ”Burnout basically means feeling locked into a job zine,” says ReRoy Spaniol, Assistant Professor of Rehabilitation seling at Boston University.2 It's related to stress, which may even aused by a single event or factor. Burnout can last for years. There :hree levels: (1) mild, with short-lived bouts of irritability, ue, worry, and frustration; (2) moderate, which is the same as mild asts two weeks or more; and (3) severe, with physical ailments such :ers, chronic back pain, and migraine headaches. Increased numbers of teacher absences have also come with more IS sick leave policies bargained by teacher unions. When the Chrissie Bamber, ”Student and Teacher Absenteeism," Phi Delta istbacks, No. 126, 7—45. Teacher Burnout: How to Cope When Your World Goes Black," nal Digest, XLIV (March, 1979), 7-10. regular teache financial. In and managerial employee had a another day or the clients 01 compelled by ' Council (MSSC‘ less eifectivr away pupil pm In 1970 emIhloyees' ab factors: urb aIcohol and d trouble, chil in job}1 It was r9594418 than The N. September, is the UTITted $1 belieVed that a P. a. Absenteeism. 4 Chris l l regular teacher is absent, there are major costs, both instructional and inancial. In most other work settings, particularly in professional nd managerial slots, when a worker is absent the work waits. If the mployee had appointments or clients to see, they are put off until nother day or covered by others already on the payroll. But students, he clients of schooling, cannot be told to come another day. They are ompelled by law to be in school. A New York Metropolitan School Study ouncil (MSSC) report showed that substitute teachers are significantly _‘EWEM‘V ess effective in classrooms than regular teachers.3 Are we bargaining ay pupil progress with more and more sick days? In T970, 56 districts in Philadelphia participated in studies of ployees' absences. Increased absenteeism was associated with these actors: urban transportation, women who take jobs for ”luxury money”, cohol and drug abuse, young hedonistic tendencies, marital and family ouble, child-care problems, extended holidays, and lack of interest job.4 It was also found that female teachers had poorer attendance ords than male teachers working in the same or similar settings. The N. E. A. published a questionnaire in ”Instructor” in the :ember, T976, issue. More than 9,000 teachers responded from across United States. Eighty—four percent of the teacher respondents aved that there are health hazards in teaching. There were three 3P. G. Elliott and D. C. Manlove, ”Cost of Skyrocketing Teacher teeism,” Phi Delta Kappa, LIX (December, T977), 269. 4Chrissie Bamber, op. cit., p. 2T. major areas 0 (3) physical - (tension, PT?- Y_ea_r: The tine-span the middle of l976-77, l??? l980-8l was o vast amount 0 LELel: school, and h iunior high 5 covered grade inside of the major areas of concern: (l) stress; (2) weight—diet-exercise; (3) physical environment. "Over and over, teachers named stress (tension, pressure) as a major force affecting their health.”5 Definition of Terms Tear: The term ”year” refers to school years that were studied. he time-span covered runs from approximately the first of September to he middle of June. The school years studied were l974—75, l975—76, 976—77, l977-78, l978—79, and l980-8l. The time lapse from l978-79 to 980-8l was necessary to allow for the compilation and treatment of the ast amount of statistical data that was considered in the study. Level: The three levels studied were elementary, junior high chool, and high school. The elementary level covered grades K-6; the Jnior high school level covered grades 7-8, and the high school level ivered grades 9—l2. District: This term refers to whether Davison teachers lived side of the Davison school district or outside of the Davison school :trict for the period of time that was studied. Employment Status: Teachers were all classified as either full- 9 or part-time employees for the duration of the study. Educational Level: Teachers were divided for educational levels he same basis as they are classified for salary purposes, that is: 5L. Landsman, ”Is Teaching Hazardous to Your Health?“ '5 Education, LXVII (April/May, T978), 50. 4. 5. A. + l5 333 A. + 30 Percent of Year Worked: Teachers were assigned according to the 'tion of the school year that they worked on the following basis: l. 2. 3. 4. 5. Less than l/4 l/4 l/2 3/4 Full time Reason for Leaving District: Those faculty members who left employ- t in the Davison Schools on either a temporary or permanent basis were egorized as to reason for leaving under the following reasons: l. Moved 2. Child—rearing leave 3. Leave of absence 4. Deceased 5. Retired 6. Professional change 7. Other Age: Teachers were grouped, for the purpose of this study, by age an-year increments. The groupings used were as follows: l. 2. 20 - 29 30 - 39 3. 40 - 49 4. 59 - 59 5. 60 — 69 Limitations of the Study The primary limitation of this study is that it was done only in e Davison Community Schools with the whole population being studied nbering 357 teachers. Studying the teacher population of one school ;trict would not be as valuable as the results of a study were the rle population of teachers being studied encompassed thousands of chers from a large number of school districts. However, the amount time that was required to go through the personnel records to gather necessary raw data precludes a multi-district study. Thus, the ults of this research can only be applied to the population that was died, teachers in the Davison Schools. . Organization of the Study The statement of the problem, the purpose of the study, some general rmation relating to teacher absenteeism, the limitations of the study, the organization of the study have been presented in Chapter I. ter II will be a review of the literature on teacher absenteeism. ter III includes a report of the research design, while Chapter IV ists of an analysis of the results. Finally, a summary of the study :he conclusions drawn, along with the implications for future research, ndertaken in Chapter V. CHAPTER II REVIEW OF THE LITERATURE Historical Information Absenteeism is not a new problem. Throughout history, organiza- tions have had to deal with the problem of short-term replacement of absent employees. Industrial managers have been much more sensitive to the impact of employee absenteeism, both in terms of dollars and pro- ductivity, than have educators. Recently, a vice-president of the Ihase Manhattan Bank commented, ”The magnitude of the problem is almost : Inbelievable. Two and one-half million workers are absent each Monday-- I ,hat is four percent of the working population."1 Private sector rates of absence due to illness fall in the 2-4 I ercent range. A New Jersey School Boards Association urban district ndicated that 66 percent of these districts exceed this 2-4 percent ange.2 A distinct trend toward increased absenteeism by employees through- It the nation has become apparent in recent years. In New York City, 1Joseph w. Lansom. How to Reduce Emplgyee AbSenteeism, Cure gginess, and Build Employee Morale (Chicago: The Dartness Corporation, . p. 4. ‘ 2Teacher Attendance Improvement Program. A Joint Business-Educator )Ject (Newark: Greater Newark Chamber of Commerce, August, 1975), p. l0. l0 bsenteeism by teachers is reported to have risen 50 percent in the past hree years, and now averages 7.5 percent each day (twice as high as the ity's office workers). At General Motors Corporation, Board Chairman )hn M. Roche reports that the monthly absenteeism rate in General Motors ’ants this year has reached 6 percent, up from 5 percent a year ago. I a given day, General Motors absenteeism may be as high as l3 percent ’ about one out of every seven or eight production workers scheduled to rk. During 1969—70 in Philadelphia, an average of 1,000 teachers were sent daily, amounting to an average of thirteen days per teacher, or a te of between 7 and 8 percent. Neither the private nor public sector seems to have been spared. 2 costs in the industrial field are alarming. Production costs spiral the quality of the product tends to go down. Accordingly, the consumer forced to pay higher retail prices or increased taxes for which he en receives a product of lesser quality in return.3 A study conducted by the Pennsylvania School Boards Association arted that the annual mean teacher absence rate was 4.7 percent. an operational level, the 4.7 percent absence rate translates into “oximately eight days of absence per teacher per year. The same isylvania study found that the trend for teacher absenteeism indicates .b .pproximate five to six percent increase between the years l96l to l978. 3Teacher Absenteeism and Related Policies for Supplemental Remunera- Philadelphia Suburban School Study Council, Pa.; South Pennsylvania ol Study Council; Pennsylvania University, Graduate School of Education, sylvania, l970; p. l. 4Teacher Absenteeism, Professional Staff Absence Report, produced ‘esearched by the Pennsylvania School Boards Association, Harrisburg, October, l978. ll A study completed for the Illinois State Board of Education showed hat there had been a 16 percent increase in the rate of teacher absentee— sm between the years 1971-72 and 1975-76.5 How Widespread Is the Problem? Extensive studies of the problem of teacher absenteeism have been impleted in Merrick, N. Y., Las Vegas, New York City, Chicago's north burban schools, California, Illinois, and Indiana. The results in ery study demonstrate a dramatic increase in teacher absenteeism. additional days are made available to teachers through collective rgaining, it appears that more of those days are being taken hy achers, and more teachers are taking those days.6 Monetary Cost of Absenteeism Substitutes for absent teaching and non—teaching personnel are a nificant portion of the budget in each school district. In a suburban veland school district of 12,000 students, in addition to the ,OO0,000 already committed to teachers' salaries, the board of educa— i expended $50,000 during the 1979 calendar year for teacher substi- 25. This was equivalent to all of the funds used to purchase Hg 5Academy for Educational Development, Public Policy Division. rigon Teacher Absenteeism in the Public Schools of Illinois to the e Board of Education. Illinois Office of Education, July, 1977). 6Donald C. Manlove and Peggy Elliott, "Absent Teachers . . . her Handicap for Students?" The Practitioner, V (May, 1979), No. 4 ton, Va.: National Association of Secondary School Principals), p. 1. l2 educational equipment that year. In 1977, another major urban school system in Ohio expended $2,933,233, or $25.50 per pupil. A Pennsylvania study estimated the costs for filling vacancies with substitutes would be in excess of $30,000,000 on a state-wide basis.7 Substitute costs are high and increase every year. A daily rate of $35.00 to $50.00 per day is not uncommon. Unfortunately, the educational ralue received for this expenditure is questionable.8 The direct cost in lost-but-paid-for labor alone exceeded twenty- ive billion dollars in 1978.9 Teacher absences cause additional financial outlays for substitute eachers and increased administrative time spent on securing replacements or absent teachers.10 The Pennsylvania School Boards Association conducted a study during ie 1977-78 school year. This project is the most comprehensive study of :s kind in the State of Pennsylvania. Its first purpose . . . to explore e basic characteristics and patterns of staff absences . . . showed that e average teacher was absent a total of 8.2 days during the school year. 5 second purpose . . . to assess the economic impact related to staff sences . . . indicated that the dual payment to the teacher and a ‘ 7James H. Capitan and others. Teacher Absenteeism. A Study of the _9_Association of Personnel Administrators, 6493 Tanglewood Lane, 'en Hills, Ohio 44131, p. 1. 81bid., p. 1. gdoseph w. Lansom, op. cit., p. 3. 10Donald C. Manlove and Peggy Elliott, op. cit., p. 5. "T‘ l3 eplacement almost doubles the cost of a day's work for the school istrict.H Pennsylvania's school districts are spending approximately 27 ’llion dollars annually for substitute teachers to keep their schools ierating during periods of short—term teacher absence, and 88 million llars in total personnel costs associated with teacher absence.12 New York City substitute teacher costs, 71.5 million dollars in 71—72, accounted for almost nine percent of the city's total expendi— . l res for teachers' salaries. 3 Instructional Costs of Teacher Absenteeism When a teacher is absent from a classroom, a substitute teacher is vided so that the student learning can continue uninterrupted. Yet, a stitute teacher, no matter how qualified, cannot carry on where the ular teacher left off. Time must be spent by the substitute teacher learning what has been previously presented or discussed, discovering t subject areas to reemphasize, and finding the particular needs of 1 child. There is, therefore, a possibility that teacher absences be disruptive to the steady scholastic progress of students. In like ier, the greater the frequency and number of teacher absences, the more P— ll 121b1d., p. 35. 13New York State Office of Education Performance Review, Teacher gteeism in New York City and the Cost Effectiveness of Substitute iers. (Albany, N. Y.: State Department of Education, 1974). Pennsylvania School Boards Association, op. cit., p. 1. l4 )portunity for retardation of learning to occur. A high teacher attend- ice would seem desirable. Should teacher attendance patterns show a elationship to weather or length of time school has been in session, a range of calendar might increase attendance, and student achievement as H.14 Many principals have been heard to observe, "If the sub can keep e lid on, that's all I ask.”15 A study conducted by the Metropolitan School Study Council of Iumbia University concluded that substitute teachers were educationally effective. This study found that regular teachers were twenty times 'e effective than substitutes in secondary classrooms. Even student chers were found to be more effective than substitutes.16 It would be safe to assume that in many districts substitutes are ected because of their availability more than they are selected for :cessful teaching”. This is not an indictment of substitute teachers, :e it is almost impossible to come into a strange classroom, on short ice, with unfamiliar students, and maintain the continuity of an iblished learning program.17 ”_— 14New York State Education Department. Teacher Attendance Patterns. flical Report No. 7 of a Study of School Calendars. (Albany, N. Y.: sion of Research, New York State Education Department, 1978), p. 1 15James H. Capitan, op. cit., p. 1. 16Martin H. Olson. "Identifying Quality in School Classrooms: Problems and Some Answers,” Central Ideas, XXI (February, 1971). 17 James H. Capitan, op. cit., p. 2. 15 Recent research has demonstrated that a significant variable in student achievement is effective time spent in instructional activities.18 Unfortunately, research and practical experience show that substi- tute teachers are less effective in keeping students "on task" than are regular teachers.19 One of the most significant pieces of research in this area is the law York Metropolitan School Study Council review of 18,000 teachers :ited above. This research showed that substitute teachers were sigpifi- gpply less effective in the classrooms than the regular teachers. brse still, the study indicated that the substitutes were less effective hen they were put in charge of a classroom. The cost in student learning when the regular teacher is absent is idoubtedly the most critical cost with which the administrator must incern himself. In one study of student achievement, researchers demon- :rated that when cutbacks occurred in school contact time there were so cutbacks in student achievement.20 Public Perception of Teacher Absenteeism Meanwhile, particularly clear to educators is the Public's growing nand for some tangible progress by students during the school year. 18Robert M. Gagne. Conditions of Learning, 3rd Edition. w York: Holt, Rhinehart & Winston, 1977). 19"Teacher Absenteeism in New York City, Etc.”, 02 C1t., P- 3- 20Annegret Harmsichfeger and David E. Wiley, ”Schooling Cutbacks VAphievement Declines: Can We Afford Them?” Administrator's Notebook, 975 . 16 he competency testing and "back to basics" movements throughout the ountry are emphatic testimony to the voting citizens' concerns for cademic accomplishment. As the equation of teacher contact time with tudent_progress becomes widely known, more hard qpestions will be asked )OUt the causes of lost instruction at school. Certainly one serious ISS occurs when regular teachers are absent and substitute teachers are rthe c1assroom.2] Student learning is the fundamental reason that schools exist. ter busing disputes, negotiations, hearings, and myriad other problems at seek resolution, the critical question which taxpayers have the right ask and for which professional educators will be held accountable is, iat happened to students who pass this way?"22 Comparison of Student and Teacher Attendance Patterns Under the present school calendar, children and teachers are stered together in classrooms from fall through spring with minor aks at New Year and Easter. The close proximity of humans is conducive :he spread of communicable diseases. One might, therefore, expect :her and pupil attendance to be somewhat parallel. Pupil attendance 5 off from the September high point to reach a low point in February, eupon the trend is reversed through June. Outside temperature and ent attendance patterns are similar. What of teacher attendance? ,_¥ 21Donald C. Manlove and Peggy Elliott, op. cit., p. 4. ZZIbid, p. 5. 17 Does it, too, follow the temperature/pupil curve? The statewide pattern showed teacher attendance to decrease to the low point in December. Thereafter, attendance fluctuated at a slightly ligher percent in attendance. Contrary to the expectations of some uperintendents, who felt the poorest attendance would occur in June hen the teachers would “take" their remaining leave, the June attendance igure was higher than the May figure. The May attendance figure was at as low as the December figure. The attendance figures of suburban eachers reached a low point in May. Generally speaking, the teacher attendance patterns do not resemble rose of the students. Though both show a decrease in attendance for the rst three months, the similarity is lost from then to the year's end. nce teacher attendance seems to be slightly related to time of year d to yearly temperature patterns, it would appear that school calendar anges would have little effect upon teacher attendance.23 Stress and Teacher Absenteeism A joint committee of a local teachers' association and the Tacoma lic Schools studied stress conditions for classroom teachers. Teachers imated the magnitude of stress for forty-four events and noted those :h they had actually experienced. ”Involuntary transfer" was perceived :he most stressful event; 17 percent of the teachers reported having I involuntarily transferred during the year of the study. The ”top stress events found in this study are as follows: __ 23New York State Education Dept., op. cit., p. 4. 18 £163.11: Bess Involuntarily transferred 1 Notification of unsatisfactory performance Colleague assaulted in school 3 Managing disruptive children 4 Disagreement with supervisor 5 Overcrowded classroom 6 Threatened with personal injury 7 Denial of promotion or advancement 8 Feeling of inability to bring about change in your building 9 Difficulty in dealing with building 10 administrator A moderately high negative correlation (-.51) was found between arted stress-induced exhaustion and days absent; a similar but posi- a correlation (.46) was found for exhaustion and the number of essful events experienced by a teacher. Major Causes of Employee Absenteeism Capitan reported that the major causes of employee absenteeism i by the participating personnel directors were: (1) personal illness; illness in the family; (3) personal leave days; (4) emergencies; emotional problems; (6) alcohol-related absences; (7) drug-related FL; 24Irene R. Mazer and Marjorie Griffin. Perceived and Experienced §_pf Teachers in a Medium-Sized Local School District. (Tacoma, ngton: Office of Health Education, Tacoma Public Schools, P. O. Box l9 absences. (It should be noted that alcohol- and drug—related absences uere reported as quite minimal.)25 Research Findings The preponderance of research indicates that teacher absenteeism s more prevalent on Mondays and Fridays. In the Ohio study of the :hool districts who computed absence on a daily basis, over half 34 percent) indicated that the frequency of absence was higher on >ndays and Fridays. The Pennsylvania study reported that the absence ,te for Friday was 5.5 percent and Monday was 5.1 percent. The remaining ys of the week were 4.5 percent or lower. Only the Birmingham, chigan, study showed any deviation from this trend, but that study vealed Monday as the day when most absences occur. The Monday-Friday idrome appears in numerous studies in the private sector, as well.26 Some of the important general findings about teacher absenteeism 1 rm the Illinois, Indiana, Nevada, and California reports indicate these tral points: - Absenteeism among all teachers increased after the enactment of collective bargaining legislation. - Demographic factors including age, gender, salary, continuous employment, and marital status do not have a significant impact on the amount of absenteeism. 25James Capitan, op. cit., p. 5. 261mm, p. 4. 20 - Absenteeism has continued to increase since the passage of collective bargaining legislation despite better pay, smaller classes, and more appropriate assignments. The highest rate of teacher absenteeism occurs the day before and the day after the weekend. High levels of absenteeism occur in school districts where there are low levels of faculty agreement toward the goals and policies of the community and school district. These high levels of absenteeism occur even in those school districts with high levels of material incentives and pleasant physical environment. Low levels of absenteeism among teachers occur in those districts with high levels of community support and policy agreement, regardless of low levels of material inducement and unpleasant physical conditions faced by teachers.27 A small percentage of teachers (10 percent to 20 percent) account 30 percent of all illness absences. Average teacher absence is comprised of 70 percent to 80 percent -term absence (five days or less). This contrasts with a 20-year, te-sector study showing that short-term absence accounts for only rcent of all illness absence. In Newark, the highest rate of short-term absence occurs in the s of January and April.28 \_ 27Donald C. Manlove and Peggy Elliott, op. cit., p. 3. 28"Teacher Attendance Improvement Program“, pp;_pi£,, P. ll. 21 The major findings of the study on teacher absenteeism in New York :y include: no apparent relationship between a teacher’s rate of ence and his performance rating. The rate of discretionary absence neteen days or less) is generally twice as high as the rate for ill- s requiring a medical certificate (twenty days or more). Teacher dis- tionary absence rates are approximately 21 percent higher for Mondays Fridays than for other school days. Discretionary absence rates are )ercent higher in Title I elementary schools than in other elementary >ols. Those schools with a higher percentage of teachers with more I five-years service show a higher absence rate from illness requiring cal certificates.29 An interesting sidelight concerns a study of administrator absences he north suburban Chicago area. The data shows the absence rate for hers to be more than three times that of administrators in the same “aphic areas and in the same school systems.30 The Pennsylvania School Board Association study conducted during 977-78 school year produced this information: - The mean work absence rate for teachers increased steadily through the school year, with a year-end mean rate of 4.75 percent. - The ”average” teacher in Pennsylvania was absent a total of 8.2 days during the 1977-78 school year. - Elementary teachers have a slightly higher absence rate than secondary teachers. \ 9New York State Office of Education, ppp_pip., p. 3. 30Donald C. Manlove and Peggy Elliott, op. cit., p. 2. 22 - Female professional staff members have a significantly higher absence rate than male professional staff members. - More absences occur on Friday than any other day of the week. - Small districts (fewer than 200 professional employees) tend to have lower absence rates than larger districts (200 employees or more). - Most effective policy in reducing teacher absenteeism appears to be requiring teachers to speak directly to the principal when reporting off work. - Using an answering service for teachers when reporting off work seems to encourage a high rate of absenteeism. — Personal sick leave accounts for approximately 69 percent of all professional staff absences. - The use of ”personal" days in May was almost twice the average rate for the school year. - Pennsylvania's absence rate has increased over 106 percent in the past sixteen years. - The mean absence rate for teachers in Pennsylvania exceeds all major industry rates determined by the U. S. Bureau of Labor Statistics and is approximately one-third higher than the national average in the education industry. - Over five-million hours of regular instructional time are "lost” due to teacher absence annually. - The study is based upon the experience of 135 school districts 23 and 25,000 employees-~an accurate reflection of statewide experience.31 The Pennsylvania study reported that female professional staff bers have a significantly higher absence rate than male professional ff members. Females have an absence rate of 5.1 percent, while males e an absence rate of 4.2 percent. This averages 7.2 days of absence 'male teachers and 8.9 days per female teacher. Married female teachers are much more likely to be absent, not y for their own illness but for the illness of their children. It 11d appear that it is much more acceptable in our society at this time ' the working wife to stay home and tend to sick children than for the ~king husband. This may be due to sex role stereotypes, or it may be .t it is easier for a working educator wife to qualify for sick leave this purpose than for the working non—educator husband. It will be eresting to observe what impact, if any, the increasing ”liberation” ur female populaton will have on this phenomena. The advent of ernity" leave, as well as ”maternity” leave, appears to be a harbinger hanges in this area. An organizational variable that seems to be directly related to her absenteeism is the size of the district. The Pennsylvania study rted that small districts had a lower rate of absenteeism than larger ricts. Size of work unit also has been verified as a major organiza- . . . 3 a1 variable in the private sector. 31Pennsylvania School Boards Association, Inc., op. cit., p. 6. 32James Capitan, op. cit., p. 7. 24 Need for Further Research No major studies have focused successfully on the correlations teen student and teacher absence rates. It is also safe to say that :her research is needed on the environmental conditions, both physical psychological, that exist in schools which might contribute to :her absence. Summary Teacher absenteeism is not a new problem. A distinct trend toward ceased absenteeism by employees throughout the nation has become arent in recent years. Extensive studies of the problem of teacher anteeism have been completed in Merrick, N. Y., Las Vegas, New York /, Philadelphia, Newark, Chicago's north suburban schools, Ohio, fornia, Illinois, and Indiana. The results in every study demonstrate amatic increase in teacher absenteeism. As additional days are made lable to teachers through collective bargaining, it appears that more hese days are being taken by teachers. Substitutes for teaching and non-teaching personnel are a signifi- portion of the budget in each school district. In a suburban land school district of 12,000 students, in addition to $12,000,000 dy committed to teachers' salaries, the board of education expended 100 during the 1979 calendar year for teacher substitutes. This was ‘alent to all of the funds used to purchase educational equipment year. In 1977, another major urban school system in Ohio expended 3,233, or $25.50 per pupil. A Pennsylvania study estimated the costs 25 lling vacancies with substitutes would be in excess of $30,000,000 tate-wide basis. Substitute costs are high and increase every year. A daily rate .00 to $50.00 per day is not uncommon. Unfortunately, the educa- value received for this expenditure is questionable. When a teacher is absent from the classroom, a substitute teacher ivided so that the student learning can continue uninterrupted. l substitute teacher, no matter how qualified, cannot carry on where egular teacher left off. A study conducted by the Metropolitan School Study Council of iia University concluded that substitute teachers were educationally active. This study found that regular teachers were twenty times rffective than substitutes in secondary classrooms. Even student rs were found to be more effective than substitutes. CHAPTER III DESIGN OF THE STUDY Theory of Involvement or Change The ultimate purpose of this study was to attempt to cause a change :itude and eventually in behavior on the part of Davison teachers ling the use of leave time. Many different individuals were red in this study; and, of course, each played a different role in lucational system. Superintendent's Role The role of a superintendent in a school system is to act as the executive of the district with ultimate responsibility to the 4 of education for what happens or fails to happen educationally in ! strict. His role in this study was to gather information and l I .ics regarding the usage of leave time by Davison teachers, as well 1 research has shown about the educational ineffectiveness of ute teachers. This information was then shared with the building hls, the Davison Education Association leadership, and the teachers. he researcher attempted to present the information to the staff a manner that the superintendent's role was not one of a "bad guy” 'itical of or making recommendations about the behavior of teachers. 26 27 s merely presenting information which anyone could recognize as for the good of Davison students and the entire Davison community. asearcher hoped that the Davison professional staff would feel that staff members who violated the professional rules about the use of time were violating the principles of the community good. anner in which the information was introduced to the staff was ied to avoid violating the ”rules of initiation" (the customary ways ich change is initiated into that organization). (See Appendix A, 222 to 225.) The superintendent then served in the capacity of an ”active” ver. The observations were made to determine if the information ted in proposed changes that were either sponsored as designed, ad and then sponsored, or rejected. This is called the "normative )rship” principle, which means that innovations or change will have ier probability of being sponsored if they are designed to meet the and to achieve the goals of the organization at that particular The researcher observed events that took place during the course 5 study and then described what he observed in Chapter IV. He ted to interpret these events in Chapter V of this study. Principal's Role he building principal serves as chief executive of a particular 9. The building principal is responsible to the superintendent 315 for the entire building, staff, and students. The principal's 28 ale in this study was to assist the superintendent in observing and rcording events that took place during the course of the study. Association's Role __________________ The Davison Education Association is the teachers' union that presents the teachers in negotiating a contract with the board of educa- )n. The D. E. A. also represents teachers in the interpretation and : enforcement of the provisions of that contract. E. A. This role places the , and its officers particularly, in a conflict relationship with h the administration and the board of education. The researcher ired the Association's endorsement and support for this study to help aring about a change in attitude and in behavior on the part of lson teachers regarding the use of leave time. If the Association's ‘ight support proved to be impossible, at least neutrality on their would be desirable. It was recognized that if the Association came in active opposition and rejected the purpose of this study, it d be very difficult not to experience opposition and rejection on the of the teaching staff. Teacher's Role The teacher's responsibility is to instruct students in the class- This is the ultimate responsibility in the educational process. ther educational responsibilities (the board, administrative, non- FlEd) are justifiable only on the basis that they have impact upon isist the classroom teacher to deliver the learning process to 29 its. The key purpose of this study was predicated upon the research ias shown that it is extremely important that the classroom teacher asent in the classroom as often as possible to fulfill these educa- l responsibilities. The purpose of this study was to accumulate "ical information regarding the use of teacher leave time in the )n district and to attempt to change teacher perceptions of the tance of their being in the classroom rather than having a substitute er there. Methodology A thorough review of the school records on teacher attendance was and a detailed summary of teacher leave information starting with 974—75 school year and going through and including l978-79 was ed. Such information as why the teacher was absent (sick day, ial day, school business, bereavement, etc.), whether they lived or outside of the school district, sex, age, grade level or subject hey taught, and whether they were full-time or part—time employees npiled. The day of the week or the month of the year in which the 2 occurred was noted. This information was collected for each teacher who had taught in 1001 district during that five-year period. A nine-page statistical ' was then prepared. A copy of this summary was given to each (See Appendix B, pages 226 to 234.) he superintendent first asked for and received the opportunity to th the Davison Education Association Executive Board in September He then met with the teaching staff on a building—by-building 30 He not only shared the statistical information in each of these ngs, but also emphasized the importance of teacher attendance in lassroom. He emphasized that a substitute should not be able to ce the classroom teacher and achieve the same results educationally tudents. He tried to emphasize the obligation that each teacher 3 students and to the community and indicated to the staff what rch has shown concerning the educational effectiveness of substitute ers. Once the information had been disseminated to the entire population studied, the following behavioral responses were observed and fled: l. Sponsorship 2. Approval, but not sponsorship 3. Neutrality 4. Inactive opposition 5. Active opposition Population Studied The population studied was the entire professional teaching staff Davison Community Schools from 1974-75 to l978-79, plus 1980-81. jects included all professional educators who were not classified nistrators. Four hundred fifty total variables were applied the subjects who were involved in the study over the entire six- “iod. Three hundred fifty—seven subjects were involved in this 31 Nature of the Data The following data was gathered on each teacher: 1. 2. 3. Sbflmmh 10. ~_| v 3 Sex School year taught Age . Name of school where assigned Level of assignment (elementary, junior high, high school) Residence (inside or outside of district) Employment status (full-time or part-time) Educational level (8. A., B. A. + 18, M. A., M. A. + 15, M. A. + 30) Grade level taught Subject area taught for secondary teachers Special education assignment (speech, social worker, L. 0., etc.) Percent of year worked ; Days on child-rearing leave . Days on long-term illness Reason for leaving district Reason for absence a. Sick day b. Personal day :. School business . Bereavement . Dock f. Jury duty 9. D. E. A. h. Military 17. Sick days by day-of-week and month—of—year. The factors listed above constitute independent variables. The data athered and compiled from information and records maintained by the 11 and personnel offices of the Davison Community Schools. Analysis Procedures va” Program The Michigan State University CDC750 computer was employed in statistical computations. The Statistical Package for the Social :es "Manova" Program was utilized to do a repeated measures analysis 'ariance with measures of percents of absenteeism repeated over six eriods. Those six time periods were the 1974-75, 1975-76, 1976-77, 3, l978—79, and 1980-81 school years. 'ests were done for main effects and interactions for three Sex Residence (inside school district vs. outside district) Level (elementary, junior high, high school) ts for the main effects and interaction were computed. The sig- 1evel at which these tests were conducted were set at = .05. Age was used as the covariate. Since treatment occurred between the fifth and sixth years, a transformation matrix was employed to obtain the contrast of the sixth ear against the other five to determine whether or not there was a reatment effect. earson Correlation Coefficients The Pearson Correlation Coefficients were used in an attempt to etermine whether or not there was a correlation for the percentage of ick leave used between months within each year for the years being udied. This statistical application was also used to determine whether ere was any significant correlation involving sick leave time used tween days of the week within each year under study. Possible corre- tions were also reviewed for reasons for absence within each year being These reasons for absence were sick leave, personal leave, udied. ave for school business, bereavement leave, dock time, jury duty, rison Education Association business, and military leave. The program used for these tests was the Statistical Package for Social Sciences at the Vogelback Computing Center at Northwestern 'ersity. Tests for Treatment Effect and for Absenteeism The treatment process used in this study was described on pages 30 of this chapter. Five sets of tests were run using the methodology outlined above Manova Program". These five sets of tests were: A set of tests for modified treatment effects, i.e., inter— 1. actions between other factors (sex, residence, level) and treatment. 2. A test for checking for interaction or a relationship between age and treatment for a particular variable, such as Tuesday, April, or illness. 3. A test for treatment effect on such variables as Tuesday, April, or illness. 4. A test for the effects of three factors on average absenteeism. The three factors were reason for absenteeism, day of the week, and month of the year. 5. A test for the relationship between age and percent of absen— teeism by reason, day, or month. Other Research Considerations One of the problems encountered during the research was the fact iany of the subjects worked for only a portion of the time period study. Thus, when results from a given year were compared to the ; f0r another year regarding a certain category being studied, the is involved in the study would vary. This problem was eliminated 9 information on only those subjects who had been present as as of the school district for all six years being studied in the cal computations. >jects who had been absent for long—term illnesses were deleted study in an attempt to more accurately depict the usual day-to- ;s patterns. 35 Subjects who had taken child-rearing and known maternity-related ess leaves were deleted from the study in an attempt to more rately portray absence for illness on the basis of sex. Comparisons illness on the basis of sex on any other basis would have been red in favor of males. Another disparity in information that had to be considered in the :arch process was the fact that the different months of the school ‘ contained a varying and unequal number of teacher work days. Thus, rould be inaccurate to compare the amount of teacher absence in another :h. This problem was overcome by determining the number of teacher < days each month for each school year. This number was then divided 3 the time missed under each category of absence for each subject to ermine the percent of absence in each category being studied. The n percent of absence was then determined for each category for the 1 number of subjects being studied. Null_Hypotheses The following are restatements of the hypotheses in null form, , the hypothesis that there is no true difference between the two groups of the population as they relate to the criteria. Ho1 There is no significant difference in the absenteeism rate between male and female teachers. Ho There is no significant relationship between absenteeism and age of teachers. 36 Ho3 There is no significant difference in the absenteeism rate of teachers who live in the Davison School District when compared to teachers who live outside the district. Ho4 There is no significant difference in the absenteeism rate for teachers in the Davison Schools regardless of whether they are assigned at the elementary level (K-6), junior high level (7-8), or senior high level (9-12). Ho5 There is no significant difference in the absenteeism rate for Davison teachers based upon days of the week. H06 There is no significant difference in the absenteeism rate for Davison teachers based upon months of the year. Summary A study was done of the reasons for teacher absence in the Davison s for a period of six school years. Data for the school years 5 to 1978-79 was summarized and shared with the entire teaching early in the 1980—81 school year. The superintendent of schools ed the importance of regular attendance by the classroom teacher ared what research has shown relative to the effectiveness of tute teachers. It was desired that the teaching staff would feel omething should be done" to decrease the amount of absenteeism taff members and would "sponsor" that concept after this treatment had taken place. he Statistical Package for the Social Sciences ”Manova” Program n utilized to do a repeated measures analysis of covariance with 37 Ares of percent of absenteeism repeated over six time periods. Since :ment occurred between the fifth and sixth years, a transformation ix was employed to obtain the contrast of the sixth year against the r five to determine whether or not there was a treatment effect. The Pearson Correlation Coefficients were also used in an attempt etermine if there were possible significant correlations between ons for absence within each year being studied. CHAPTER IV ANALYSIS OF THE RESULTS This chapter will include the results of the experimental design, 5 well as the statistical findings of the study, along with the analysis ‘d discussion of those findings. Results will be presented in the same der in which the study was outlined in Chapter III. The results of e experimental design will be described first, followed by the results the tests of the hypotheses in the same order in which the hypotheses re presented in Chapter III: Experimental Desigp The staff subdivisions which were studied were all integral parts the Davison Community Schools' formal hierarchy with the exception of Davison Education Association Executive Board. This Executive Board an autonomous group completely outside of the official sphere of rol of the Davison Schools. This group of staff members serving as ). E. A. Executive Board was an official subdivision of the Michigan tion Association and was accountable only to the M. E. A. and their nion members of their actions as Executive Board members. The researcher compiled information and statistics regarding the of leave time by Davison teachers, as well as what research has 38 39 shown concerning the educational ineffectiveness of substitute teachers (see Appendix B). This information was then shared with the building principals, the Davison Education Association leadership, and the teachers. It was hoped that the Davison professional staff would react to the information by recognizing that a reduction in the use of eacher leave time would be beneficial to Davison students and the avison Community. It was also hoped that the staff would sponsor the elief that "something needed to be done” to reduce absenteeism, and that hose staff members who violated the professional rules about the use of eave time were violating the principles of the community good (see ppendix A). The response of the Davison Schools' professional staff to informa— ion and statistics concerning staff absenteeism presented by the esearcher is summarized in Table 4.1. The researcher relied upon )servations of the building principals, as well as his own reactions, to etermine where the response of the various sub-groups of the Davison hools' professional staff would be depicted in Table 4.1. Perceptions the response to the various groups, both on the part of the researcher i administrative personnel, are, of course, highly subjective. Some ef obserVations concerning the reactions of these subdivisions of the ison professional staff are: p93 Education Association Executive Board This group was very polite and attentive during the course of the antation. Questions that were raised were open and appeared to be sincere. The researcher detected a small degree of ”defensiveness” 4O x x wusum Hoocom cop: poaeom ilillia.llr x x mumum Hoosom 2mg: wowczw x x mumum xumucmsoam uuooaoz x x uuwum humucwewam comEose illellllllllllliTlli iII1lllllllllllllllllllllil: x x wumum sueucweoam mamem .Tlll .llililllllllli illlIlllllllllllllllllllllllll x x wmmum xumucwemam wumummuaziaafl: Iiillllllllllll x x iIlIll1Illllllllrlllllliillllili wumum xumucmswam mmumw I iiilliiiiii+iliiliilll- meum >HMHC®EQHW Hflhgch . oumom w>wuzowxm .<.m.o riff; oz umnz no» copuemomdo seeuemomdo aauusoz “Oncomm oped illiiiilliiilliilriiiiri111111. thom d>wpo< m>wuomcH :memm #02 use tHoHuumm . ahrmmma can iiiilidMMMAddfiiiliii. o>0poa< ace . imeienma .hhiwhma .oeimnma mum: ::0wuwfiufi:H nowcoam mm:vnmamu0u mews w>moq ummum 1 HUHM 0 CO . page mo>flooumm u mum u um Hmowuoumq: cw>awowm 0H . a .53 mCOMmfl>ficnsm mumum mmcmgo m mchOmcogm cw meek m>mm4 we mm: asp mncmzok mew eeeem possum es pee ling 95m: weepm mo m a F Em>Fo>cH mgp mcw>cmmao Lee wvmaw.wwmmwmwzcm .— Jq $.35. 41 on the part of certain individuals when questions or comments such as, "Why are you gathering statistical information on teacher absenteeism?” "Why don't you study absenteeism among administrators instead?” or "I think if you will compare the rate of absenteeism among teachers to the rate of absenteeism among shopworkers that you will find that teacher absenteeism is much lower,” were raised. The researcher has received no information either during the course of that meeting or since that time that would allow him to classify this group as anything but ”neutral” as to the response to the information presented. Central Elementary Staff This staff also appeared to be interested in the information pre- sented by the researcher but had hardly any questions or comments at the conclusion of the presentation. A few individuals later laughed about the presentation and felt that it was a joke. (Ironically, these staff embers tend to be absent more often than the average teacher.) Even ith this small amount of negative response, both the building principal nd the researcher agreed that the staff as a whole should be classified 5 ”neutral” in response to the staff-leave information. ates Elementary Staff The Gates staff appeared to be receptive to the information that 5 presented. A small amount of discussion followed the presentation, d some questions were raised concerning the data. There was discussion tween small groups of teachers later that same day and during subsequent ys concerning the content of the presentation. Comments were heard ch as, "That was really an interesting study,” ”It touched on a lot of 42 areas,” and "It makes us look pretty good." This last observation referred to the fact that teachers used only approximately eight of the ten days allocated to them. The Gates staff was categorized as ”neutral” in response to the staff-leave information. Hill-Uptegraff Staff This staff seemed to verbalize more during the course of the presentation than did other staff groups. They seemed to personally identify with different types of leave information presented. Staff members were open and receptive to the presentation but appeared to have little comment afterward other than that “it was interesting”. The Hill— Uptegraff staff was classified as being ”neutral”. Siple Elementary School Staff This staff was evidently receptive to the information presented by the researcher. The building principal felt that the presentation helped to reinforce and strengthen the resolve of those teachers with good uttendance records. These individuals would verbalize that this (good ,ttendance) was part of their contribution to the educational process and o a good educational system. It further encouraged them not to use heir days for absence unwisely. The dedication of these individuals can a illustrated by the comment, I'I need to be there. I need to teach lat subject-verb agreement.” Obviously, not all members of the staff felt this way, and some ntinued to use leave time. The principal did report, however, that more an one staff member would preface their request for leave time with, feel quilty about having to use this day after that report, but. . . ." 43 Both the building principal and the researcher felt that the Siple School staff should be classified under ”approve but not sponsor” in its response to the staff-leave information. Thomson Elementary Staff The Thomson staff was courteous and attentive during the presenta- tion but had very little comment at its conclusion. There appeared to be minimal comment or discussion among staff members relative to the information shared by the researcher subsequent to his presentation. The Thomson staff was categorized as ”neutral" in its response to this information. Wolcott Elementary Staff The Wolcott staff was accepting of the information presented by the researcher. There was some discussion and there were also questions immediately after the presentation, but a minimal amount of discussion of :he subject matter during days or weeks subsequent to the presentation. ’here was no change in the absenteeism pattern of Wolcott staff members. he Wolcott staff was classified as "neutral" in response to the staff— eave information presented. gpior High School Staff The presentation to the junior high school staff was the only time at the researcher felt a negative response on the part of his audience. e response of the staff appeared to be one of resentment and even :agonism. Eye contact was minimal or non-existent, and ”body language” 'icated that the information was not well received. The researcher can 44 best describe his feelings as being comparable to those feelings that he has experienced while making millage presentations to a hostile audience. There were no overtly hostile reactions on the part of the junior high school staff to the inf0rmation presented. There was a complete absence of questions or comments. The building principal indicated to the researcher that the junior high school staff felt that we were ”checking up” on them because of the nature of the information that had been accumulated. He stated that the taff felt that the principal had no right to question them as to their easons for absence. One teacher even told the principal directly that 1e was taking a sick day, and the principal had no right to question him iS to why! The principal, of.course, took immediate exception to that itatement. The building principal and the researcher both agreed that the esponse of the junior high school staff to the staff-leave information hould be classified as ”inactive opposition". gpior High School Staff The high school staff was the largest single segment of the profes— onal staff with whom the researcher met. The staff numbered nearly 100 rsons, and the presentation was made in the high school auditorium. a staff was polite and attentive, and there was an exchange of ques- ins and comments at the conclusion of the presentation. One staff Iber took the time to write some suggestions to the presenter on how accuracy of the statistical summary might be improved and sent them the researcher through the interschool mail. Those suggestions were oful and appreciated. 45 The building principal indicated that several staff members stated that the information was ”interesting”, and that a number of informal discussions took place relative to the data presented during the days immediately following the meeting with the staff. Some members of the high school staff informally indicated to an administrator that some individuals used their illness days frivolously iecause of the existence of the Teacher Sick Bank Program. These indi— iduals felt that they no longer had to save their days for an emergency” because the Sick Bank ”would take care of them”. The principal felt that a significant number of his staff members hould be classified as ”approve but not sponsor” in response to the :aff—leave information, and that the remainder of the staff should be itegorized as ”neutral“. The response of the staff was ultimately scribed as ”neutral”. aff Overview The overall response of the Davison Schools' professional staff the staff-leave information has to be classified as “remain neutral”. 2 behavior of staff members toward the use of leave time was unchanged the staff—leave information imparted to them by the researcher. ff response to this information will be analyzed in detail later in ; chapter. The information concerning staff—leave was given openly consistently to the various staff subdivisions. No attempt was made ircumvent the formal structure of either the Davison Education ciation or any other subdivision within the professional staff. per the researcher nor any other administrator contacted during the 46 urse of the study felt that the professional staff or any subdivision ereof perceived thatthe "rules of initiation” were violated. Treatment The terms “treatment” and ”treatment effect” will be used exten- vely in Chapter IV. The term ”treatment“ is used to refer to the cess wherein the researcher met with the Davison Education Association cutive Board and, later, the entire professional staff on a building- building basis. The researcher shared statistical information with ff members regarding teacher absence in the Davison Schools for the 001 years 1974-75 to l978-79, as well as research information on the cational effectiveness of substitute teachers. A copy of this brmation is located in the Appendix. The term ”treatment effect” refers to whether or not in fact there any effect or change in the rate of teacher absenteeism during the 1—81 school year as a result of the “treatment”. Tests for Treatment Effects The researcher tested modified treatment effects to find out her there was a significant interaction between sex, level, or dis- t of residence of Davison Schools' professional staff and the :ment. This test was conducted for days of the week, months of the . and reasons for absence. Repeated measures analysis of covariance measures of percents of absenteeism repeated over six time periods 47 nas used. The significance level at which these tests were conducted as set at a (alpha) = .05. Analysis of variance was also used to determine whether or not: A. There was a significant relationship between age and the effect of the treatment. B. There was a significant treatment effect. These two tests were also applied against days of the week, months f the year, and reasons for absence. Univariate F-Tests with (1.90) F. were used to test these relationships. The percentage of absence i r each year was compared to the percentage of absence for the previous er in this process until ultimately the percentage of absence for 80—81 was compared to a composite percentage of absence for the five- ar period (1974-75 to l978-79) to determine treatment effect. The sig- ficance level at which these tests were conducted was set at 6 (alpha) 05. Results of the Tests for Treatment Effects ; of the Week, Tests for Treatment Effect Univariate F—Tests with (1.90) D. F. were used to test for signifi— . treatment effects for each day of the week. The Significance of F the percentage of absence for 1980—81 (P80) indicated whether or not e was a significant treatment effect for that particular day. The ificance level at which these tests were conducted was set at lpha) = .05. Table 4.2 shows that the Significance of F for Mondays was .68017. Therefore, there was no significant treatment effect for Mondays. Table 4.3 shows that the Significance of F for Tuesdays was .55492. Therefore, there was no significant treatment effect for Tuesdays. Table 4.4 shows that the Significance of F for Wednesdays was .52533. Therefore, there was no significant treatment effect for Wednesdays. Table 4.5 shows that the Significance of F for Thursdays was .85549. Therefore, there was no significant treatment effect for Thursdays. Table 4.6 shows that the Significance of F for Friday was .63555. herefore, there was no significant treatment effect for Friday. In summary, these tests indicate that there was no significant :reatment effect for any day of the week. pyp of the Week, Modified Treatment Effects Analysis of variance was used to test for modified treatment ffects or interactions between sex, level, and district of residence 1d treatment. The significance level at which these tests were con- rcted was set at a (alpha) = .05. Table 4.7 shows that there was a significant interaction between vel and effect of treatment for Mondays. Significance of F for absence level on Mondays was .01937. This significant interaction caused the searcher to look at staff absence on Monday by level in greater depth. 49 H mmmwp. mmvvm._ mQFQO. omFOO. momma. omFOQ. mm; mommm. vmwom._ ommoo. owmoo. mm—mm. owmoo. on; woomm. mmwom. FFOFQ. NFMOQ. OMOFm. N—moo. mum o_mmm. wNFNw. mamFQ. mooro. mommc._ mow_o. mm; wamm. ONme. mmmwo. wMOFO. mmmmm.w wmopo. own a 40 a . m cam: . m so Sam . m we Ezm wocmu_ew:m_m Loccm mwmwcuoqzz Loccm mwmmcpoazz Hi/ .a .e nom._v see; mpmse-a eeeeee>_e= .mseemese toe eeeeem peaEeeaae toe ease .m.e e_eee H mpmwgm> ovmmm. mwmvo. ONFOO. moooo. waOF. moooo. mm; Nommm. Ammoo. wvmoo. moooo. mwmmv. moooo. mm; ovmmk. comm”. mmmoo. m—Foo. Nmoom. m—Foo. mum wwmmm. _mmmv._ omwFO. axmmo. omqm©._ «Ammo. mum mpomm. vQFNF. m—omo. ofimoo. awn—m.m m_moo. om; a go a . m sea: . m new: . m eo Eam . m 40 Ezm mpmwgm> mesmmewcmem Loccm mwmwcpoazz Locsm mwmwnpoqaz .L .2 \Dh._/ 23...; 0:1). . )ii. .1. . i 50 1H momme. emcee. me_oo. eeooo. eemm_. @8000. was mNN_N. Nemem._ mmmoo. Reece. mmmwm. Reece. mes w_emm. seems. Reece. mmeoo. omwee. weeoo. ems memes. Neeee. moo_o. Reece. Nweom. Reece. wee mammwwu emmmo. mmm_o. eeooo. __eme._ eeooo. owe a +6 a . m :mmz . m so Eam wocmoww_cmem Loccm mwmwzpoaxz Logcm mwmwgwoaxz HH .d.a Aom._v cue; memohid mpmecm>ecz .mmemcagh com Homewm pcmapmmch Low pmwp .m.¢ wpnmp H memecm> mmqmu. mmmwo. NQFQQ. oFooo. mmmmo. OFOOO. mum mmmmm. mwmoq. vmmoo. om—oo. mmrmm. omroo. mmm om—mm. m—mm—. vmmoo. qmpoo. mmwmm. ¢m_oo. mum @womm. mmwFQ. @mmFQ. mmooo. ommmm._ mmooo. mm; mmmmm. mmoow. cam—o. womoo. mmwmm.p womoo. om; a mo a . m 28w: . m we Ezm . m 4o Ezm opwwgw> wocmoww_cmwm Loccm wwmmcuoazz Locem mwmmcpoa>r H .L .2 «Dbl, .31; 0300. _ 11.5.1.3; . a 51 . a es a .o mocoowmwcmem Loscm memocpoozz Loccm memocpoozz H vwmfim. wowoo. mmpoo. Foooo. mom—F. Foooo. mm; momma. m©_eo. mmvoo. Foooo. mmmmw. Foooo. on; ommmm. FmFNm.F wwN—o. meFQ. _omm_._ moo—o. nmo ¢NF¢w. mmovo. com—o. . Pwooo. wmmvm.— Fmooo. wk; mmmmm. vFQNN. vmwmo. mmmoo. vwmmm.m mmmoo. own . m coo: . m so Eom . m wo Eom opowco> .a .o “om._v gees memee-a eeeese>ee2 .mseeesa see eeaeeo oesEeeeee see ease .o.e e_eee 52 emomm. momma. NNmNo. N eeomo. eeseemeo ea _e>eo me xem eNNom. Neeem. ooN_o. N ooemo. eeeeemee an _e>ea NNNNN. NNeNo. moNoo. _ moNoo. eeseemso as xem eooNo. onNe. Noe_o. N omoNo. _a>eo xe xem mmeem. ooPmN. NNNNo. s NoNNo. peeeemeo emmso. mNNm_.e m_mN_. N NNNmN. _essa NNNNN. ooNNN. omNNo. _ omNNo. xem a so u osmoom .d .o moeooom cospossmm oocoossscmsm coo: so Eom so oocoom .N.e asses .mzoocoz :o mpoossm pooEpooLs oosssooz Los poms 53 Table 4.8 shows the mean percentage of absence on Mondays and lard deviations by level for the six years studied. The following usions were derived from Table 4.8: 1. Elementary teachers were absent a greater amount of time than teachers at the other two levels during four of the six years studied. They missed the second greatest amount of time the other two years. 2. Junior high school teachers were absent the greatest amount of time on Mondays for two of the six years studied, missed the second greatest amount of time during three of those years, and missed the least amount of time during one year. 3. High school teachers were absent the least amount of time as compared to junior high school and elementary teachers during five of the six years studied, and missed the second greatest amount of time the other year. The researcher has to assume that the reason for the significant action between level and effect of the treatment for Mondays was the high school staff missed the second greatest amount of time by for absence on Mondays in 1980-81, when they had missed the least of time for absence on Mondays for the other five years that tudied. Table 4.9 compares the percentage of absence for elementary, high school, and high school staff members on Mondays for the six 1 studied. Elementary teachers were absent the greatest amount of ; 3.99 percent) on Mondays, junior high school teachers the second 54 Hoozom memo. oNno. neNo. ooeo. oeNo. meNo. oeNo. mNNo. semo. oeNo. ooNo. omNo. son: uoecum Hoozom ooNo. eNNo. oNeo. mmmo. Nmeo. ono. eeeo. eeeo. ooNo. ammo. osmo. memo. now: poecso Nmmo. memo. mono. emeo. momow ooeo. memo. ommo. oNeo. oeeo. ono. ommo. sueecueeam COHumHsmom o o o o l . “0.. oNNo NNNo memo. ono. mono. eomo. some. memo. mono. Nmmo. oemo Nomo apescu o .>oo .oum cam: .>oo .oum one: .>oo .oum see: .>oo .oum :eez nummrnmmm can: .>oo .oum can: Ne>oo Noioooe apropos oeieeme seioeoe mmwmeme plasma z .m.¢ o—oos msoo> xo so>oo An ozoo coxosm cos: mzoocoz Los oocomo< so omopooocoo 55 oeNo. omoo. oooo. eeez owes. NesN. moNo. _eoes ono. eNNo. memo. so-ooo_ wmso. mmmo. mmvo. msuwmms meNo. oNoo. ooeo. oN-NNos oNNo. oeeo. oomo. Ne-oeos come. some. oooo. osnmsms omNo. osmo. ommo. me-eeos opom mooomo< coo: opom oooomo< coo: opom oooomo< coo: Low». soozom cos: coscom soosom gas: Losooo xsopcoEo—m mxoocoz on so>oo so ozoo :oxocm cos: oooomo< ssopm cos coo> x o mcooz so mossossom .m.o osoos 56 eatest amount of time (3.58 percent), and high school teachers the ast amount of time (2.48 percent) on Mondays. Table 4.10 indicates that there was no significant interaction :ween sex, level, and district of residence and the effect of the iatment on Tuesdays. Significance of F for staff absence on Tuesdays well above the a (alpha) = .05 level for every variable. Table 4.11 illustrates that there was no significant interaction ween sex, level, and district of residence and the effect of the atment on Wednesdays. The significance level was above the d (alpha) )5 in the case of every variable. Table 4.12 shows that there was a significant interaction between 51 and effect of treatment on Thursdays. Significance of F for ince by level on Thursdays was .01688. This significant interaction ed the researcher to look at staff absence on Thursdays by level in ter depth. Table 4.13 shows the mean percentage of absence on Thursdays and iard deviations by level for the six years studied. The following iusions were derived from Table 4.13: 1. Elementary teachers were absent on Thursdays a greater amount of time than teachers at the other two levels during only one of the six years, and that year was 1980—81. They missed the second greatest amount of time during four of those years and missed the least amount of time during one of the years studied, 1976-77. 2. Junior high school staff members were absent the greatest amount of time on Thursdays when compared to the other two 57 H Nooom. oeoso. NeNso. N moeNo. ooseemso so so>ao so xom me_oo. omoeo. ooooo. N mooso. ooseomso so se>eo oeooN. eN_No. smsoo. _ _msoo. oossomso so xem oNe_o. osooo. mo_oo. N onoo. se>eo so xem Nmoos. omemo.N emNmo. _ emsmo. eoseomso sooNo. NNsNo. omooo. N NNooo. so>ao oooeN. mssoo._ NoeNo. _ NoeNo. xam s so osoo m .s .o mocoo m cosposso> oocoosssomsm coo: so Eom o oucoom HH meeomeeoez :0 moeasso possesses oesssooz cos ewes .__.e asses wamm. smmnm. oomoo. . m msmso. pustmso an sw>w4 An xwm mmmom. ommmm.s wmmso. N mmmmo. pusgpwso an sw>w4 Nmomn. mmwwo. wmwoo. s wmmoo. posspmso An xmm mwmmo. smomm.m ovmoo. N swwms. sm>w4 An xmm oqmms. mmwom.m momoo. s mommo. possumso assoc. vmmom. mmwso. m vvmmo. sw>w4 mmmmm. mooo_._ mswmo. — msmmo. xmm s so s ago: m .s .o mason m cosposgo> mocoosssomsm coo: so Eom so ooeoom HHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHwi1iIIiilliililiilliiilllliiii 58 ooeoo. _sNeo. soooo. N Nosoo. oeseemso so _e>eo so xom mssms. ommsn. mmmso. N ossmo. poscomso so so>oo osmoo. smooo.m osmoo. s osmoo. oosgpmso so xom mommm. mooom. mow—o. m Nmsmo. so>m4 xo xom amass. mmoom. omooo. s osmoo. posgpmso wmoso. mmmmm.o mmmwo. N mamas. so>oo m—ooo. ooomm.m Nswoo. s Nswmo. xom a so o ooooom .a .Q mosooom cospossmm moooossscmsm coo: so Eom so oosoom mxoomcocs eo moeasso seasoeoes oosssooz cos owes .N_.e esoes 59 omNo. NoHo. NsNo. ANNo. eNmo. NmNo. ono. HNNo. oomo. osmo. oeNo. oNoo. mNmo. homo. moeo. oNNo. oeNo. ooNo. ommo. moeo. oNNo. osNo. mNmo. oooo. HNNo. NNNo. ooNo. somo. NoNo. ooNo. ooNo. memo. NNmo. soNo. NNNo. osNo. ano .omw coo: .>oo .oum coo: .>oo .oum oeoz .>oo .owm woo: .>oo .oum NoioooN apropos mmissom seioeom osioeoa Home. vao. ammo. mhmo. :moz ooNo. oeNo. oemo. momo. somo. Homo. ooNo. osmo. .>oo .oum cow: moioooa lIai' Ill Hoocom :mfl: newcom Hoocom :ma: “Cacao >umucmEmHm coauMHJQOL wuwuca uom ~w>vq memos so so>wo an czoo coxocm cog: mxoomcocs cos oocomo< so omopcoocoo .ms.¢.mo—oos. 60 levels during four of the six years studied. They missed the second most amount of time during 1980-81 and the least amount of time during 1975-76. 3. High School teachers were absent the greatest amount of time on Thursdays when compared to the other two levels only during the 1975-76 school year. This staff used the second greatest amount of time during 1976-77 and used the least amount of time for absence during the other four years of the study. The researcher believes that the reason for the significant inter— tion between level and the effect of the treatment for Thursdays was at the elementary staff missed the greatest amount of time for 1980-81, d that was the only year in the study that this occurred on Thursday. a junior high school staff also missed the second greatest amount of ne for absence on Thursdays in 1980-81. This was also the only year : of the six years of the study that this occurred. Table 4.14 compares the percentage of absence for elementary, ior high school, and high school staff members on Thursdays for the -year period studied. Junior high school teachers were absent the atest amount of time (3.02 percent) on Thursdays, elementary teachers second greatest amount of time (2.95 percent), and high school :hers were absent the least amount of time (2.38 percent) on Thursdays. Table 4.15 illustrates that there was no significant interaction teen sex, level, and district of residence and the effect of the .tment on Fridays. The significance level was above the a (alpha) 5 in the case of every variable. 61 wmmo. Nome. mmmo. coo: owes. ssws. onus. ropes mm—o. some. mswo. smuomms smmo. mmmo. wmmo. mmuwmm— meo. mmvo. memo. wmummm— smmo. owmo. msmo. Kurosa— smmo. «mmo. ammo. omnmmms mvwo. mmmo. swmo. mmivsms iiiopom oocomo< coo: opom oocmmo< coo: opom wocomo< coo: Loo> soocom gas: soscom soocom gas: Loscoo zeopcwaosm mxoomeogs so so>m4 so czoo coxocm cog: oocomo< ssopm Los Loo> An mcooz so mossoesom .¢_.¢ msnos 62 smomw. mmows. msmoo. N omsso. posspmso so so>o4 so xom osmmm. oNsoo. ooooo. N moooo. posgpmso on so>oo asses. msomo. wNNoo. _ wsNoo. poscpmso on xom osmos. Nsmom. ssoso. N sosNo. so>o4 an xom mmmoN. mmovm.s mosoo. s sosoo. pusspmso mssmw. msNos. oovoo. . N smwoo. so>oo mosmw. oMNso. smsoo. s _msoo. xom ii, a so a osooom .s .o mosooom cosposso> mocoossscmsm coo: so Eom so musoom osmosso eo mooosso possesses oosssooz cos owes .m_.e o_oos 63 Days of the Week, Test for Interaction Between Age and Treatment Univariate F-Tests were used to test for interaction between age and treatment. This test was run for each day of the week. The Signifi- cance of F for the percentage of absence for 1980-81 (P80) as compared to the composite percentage of' absence for 1974-75 to l978-79 indicated whether or not there was a significant interaction between age and treat- ment for the particular day being tested. The significance level at which these tests were conducted was set at 6 (alpha) = .05. Table 4.16 shows that the Significance of F for Mondays was .75083. Therefore, there was no significant interaction between age and the treatment for Monday. Table 4.17 indicates that the Significance of F for Tuesdays was .61749. Since this significance level is not below 6 (alpha) = .05, there is no significant interaction between age and the treatment for Tuesdays. Table 4.18 illustrates that the Significance of F for Wednesdays is .88855. Therefore, there was no significant interaction between age and the treatment for Wednesdays. Table 4.19 shows that the Significance of F for Thursdays was .74256. lince this significance level is not below a (alpha) = .05, there is no ignificant interaction between age and the treatment for Thursdays. Table 4.20 indicates that the Significance of F for Fridays was 85762. Therefore, there was no interaction between age and the treat- ent for Fridays. In summary, these tests show that there was no interaction between e and the treatment for any day of the week. 64 msNom. omomm._ mosoo. smvms. mm; ommms. smmmw.s omNoo. mmmvs. mm; oommm. vmmms. ssoso. mwsvo. ska mmwvv. mmwmm. quso. ommmo. ms; mom—o. ossmN. mmmmo. msto. own u so a oases m N as sosoz oneseo> oocoossscmsm coo: Loesm .s .Q Aom.sv :psz momosim oposco>so3 .mooomoos cos pcospooss ooo wm< cooZHom cospoosoch Los “mos .ms.¢ osoos ems—N. vqsms. omsoo. mswmo. mmo ammom. wmwoo. wvmoo. oomoo. as; mmsmm. Nsooo. mwwoo. mssoo. mmo ommom. mmmmm.s omwso. ommms. wmo mmomm. moses. msomo. mmmmo. own a so a oases m N o— sosoz seesce> oocoossscmsm coo: Lossm .L .2 «:h.: .32; mpmwTL wum...u>_:3 6553:): 1. TL 65 smmov. mmvmm. mqsoo. . mwmso. mum oqmss. mmomm.m NNmoo. mNmms. aka Nmsom. omwmm. meoo. mmsoo. mum mmosm. snows. moose. vmwoo. mum ommvm. omwos. mNmso. smsmo. om; s so u oocoo m m ms spsoz oposso> oocoossscmsm coo: LoLLm .m .o Aom.sv zpsz osmosis oposco>scz .mooomcogs cos pooaooocs coo om< coospom cospooeoch Los poms .ms.o osoos 1H Nswmm. mwmso. Rosco. mwooo. msm mwvmm. s—omm. ommoo. Nwooo. on; mmmom. Nmmqs. wmmoo. mNovo. mmo wmmmw. stmo. ommso. NNmso. wmo mmwww. mmmso. com—o. swwso. omo a so a oases m o 2 .532 Bets, ooooossscmsm coo: Locgm .. .3 \D}..a I). anU_|. U)3..S....> .1) 66 scams. mssss. Nmsoo. Nsmmo. ms; mmvmw. mmvmo. movoo. momso. on; somos. mammw. wwwso. momwo. mm; Nwmwm. mmsvs. ommmo. smsoo. mum Nonmm. mmmmo. swwmo. mow—o. own N so N ooeeo m N 2 .532 Bots, oocoossszmsm coo: cossm .N .Q Aom.sv cps: mpmosus oposso>soz .mzoosgo Nos ucprooLs oco om< coozpom cosponsoscs Nos poms .ON.v o—oos 67 iths of the Year, Tests for Treatment Effect ___._______________N________________________ Univariate F-Tests with (1.90) D. F. were also used to test for inificant treatment effects for each month of the year. The Significance F for the percentage of absence for 1980-81 (P80) as compared to the posite percentage of absence for 1974—75 to l978-79 indicated whether not there was a significant treatment effect for that particular month. significance level at which these tests were conducted was set at alpha) = .05. Table 4.21 indicates that the Significance of F for September was 46. Since the significance level is not below a (alpha) = .05, there not any treatment effect for September. Table 4.22 shows that the Significance of F for October was .17428. efore, there was no significant treatment for October. Table 4.23 indicates that the Significance of F for November was )2. Therefore, there was no treatment effect for November. Table 4.24 illustrates that the Significance of F for December was 12. Since the significance level is not below 6 (alpha) = .05, there 0 significant treatment effect for December. Table 4.25 indicates that there was a significant treatment effect anuary, since the Significance of F was .01406. The researcher zed the absence statistics for the months of January and can explain ignificant treatment effect only on the basis that the mean absence ‘ncreased from 2.04 percent in l978-79 to 3.31 percent in 1980—81. »ex, and district of residence also had statistically significant 5 in January, but those results will be discussed later in this Y‘. 68 mammm. moooo. mmwoo. ooooo. wosmm. ooooo. mmo omomm. smsoo. mmwoo. soooo. osmnm. soooo. mm; moosn. msmms. Nommo. mmqoo. NNNnm.N mmwoo. mum msmmm. msmom._ mmmmo. oommo. ommwm.m ovmmo. wsm mmvss. smmkm.s sovoo. mooms. mvmmm.m mooms. own N so N . m coo: . m so Eom . m so Eom ooooossscmsm coccm msmwzpoozz coccm osmocpoozz nHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH .N .o Aoo._o Nose memos-c oposco>seo .coooooo cos ooosso oeoEpoocs cos owes .NN.e osoos wmmmm. momwm. vomoo. masoo. oposco> mmmws. masoo. mm; mmmmm. mwmmm. szoo. moNoo. owNmN. mmNoo. om; vsmmm. mmmoo. mmmoo. moooo. womom. moooo. ska womoo. wommm.m msmmo. mmvms. mmmmm.m mowms. mm; mvsmm. mmmmm. om—No. qmwso. «NNNm.s vmwso. own s so s . m coo: . m coo: . m so Eom . m so Eom mposco> oozoossscmsm coccm osmocpoooz coccm osmocpoooz HHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH .s .Q Aom.sv cps: mumos-s mposco>sc2 .conosoom cos poossu powspooc_ ca. 500. ..i.. 1.1. 69 mmmww. memmv. mmvoo. mNNoo. msmov. oNNoo. mum momwo. owmmN.v wwwso. vamo. vmmmm.s N¢wmo. mum mNowm. Nmooo. vsmmo. Noooo. NMNN©.N Noooo. NAN oomww. vosmo. moswo. _msoo. mommm.m smsoo. me Nmem. omsoo. voomo. ovooo. mommo.m ovooo. owN N so N m coo: wcoo m so Eom . m so Eom oposco> oocoossscmsm coccm osmozsooxz coccm osmogpoozx .N .o coo..v No.2 memos-N ooesce>seo .cooEoooo cos eoosso eeoeoeocs cos owes .eN.e o.oes oomoo. mommw.m mmsoo. wmmoo. mamas. vmmoo. mum Nmmmm. smNNN. mvsoo. mmsoo. moosm. mmsoo. mum mmmmw. omvsv.s Nsmmo. mmwmo. mwowq.m mmmmo. ANN owsmo. qwmmm.v msmmo. mmmsm. vsmvo.m wmmsm. me Nommm. mwoms. ONFON. ommmo. waos.ws ommmo. owN N so N . m :ooz ocoo m so Eom . m so Eom woosco> moooosssomsm coccm osmocpoooz coch osmoconN: .L .2 \Dh._g 2...: 7:7). . I- 7O vamm. mwosm. momoo. sosoo. Ommmv. smsoo. mso ommws. om—ws.s Nmmso. Nmmmo. omwms.s Nmmmo. omo momms. Nmmso.N Nmmvo. osmwo. owwvw.m osowo. sum mmmvm. mmsmw. mwmmo. vmsmo. wmvmm.m vmsmo. mum movso. vamN.m mmsmo. smst. Nmmso.¢ smsmm. owN N so . m so Eom . m so Eom oposco> moooosssomsm coccm $858»: coccm osmofioocf .N .o 8...: it. SmasN Besceieo .ocooeoo cos peas: oeoeeeocs cos has ANN... Boos 71 Table 4.26 shows that there was no treatment effect for February, since the Significance of F is .84514. Table 4.27 illustrates that the Significance of F for March was .23706. Since the significance level is not less than 6 (alpha) = .05, there was not any treatment effect for March. Table 4.28 shows that there was no treatment effect for April, since the Significance of F is .40789. Table 4.29 indicates that there was no treatment effect for May, since the Significance of F is .35857. Table 4.30 illustrates that the Significance of F for June was .67147. Since the significance level is not less than 6 (alpha) = .05, there was not any treatment effect for June. Months of the Year, Modified Treatment Effects __N______________N__.________________________ Analysis of variance was also used to test for modified treatment effects or interactions between sex, level, and district of residence and treatment. The significance level at which these tests were con— lucted was set at a (alpha) = .05. Table 4.31 shows that there was a significant interaction between ex and the effect of the treatment for September. Significance of F or absence by sex in September was .01295. This significant interaction aused the researcher to look at staff absence by sex in September in “eater detail. Table 4.32 shows the mean percentage of absence and standard devia- Ons by sex in September for the six years studied. The following nclusions were drawn from the information presented in Table 4.32: 72 NNmsm. stoo.s momoo. osmoo. mNmNN. osmoo. mNN wvoos. Names. Nsmso. mmsoo. mmows._ mmsoo. oNN mwowo. omsss.m sawmo. mNst. mmsom.m szNs. NNN smomv. oommm. oommo. sea—o. swme.m swmso. NNN monN. mwmsv.s comma. NNmmo. mommm.m NNmmo. owN N so . m cow: m so Eom .om coo: . m so Eom oposco> oocoossscmsm coch osmocpooaz coccm msmocquAI H .N.Q Aom.sv cps; mpmwsiN oposco>scz .cucoz cos womssm pcpromcH cos pmwh .NN.¢ wsnos H ooNNo. oommm.m NNmoo. omwNo. mmmno. omwNo. mNN mmsso. moooN. sosso. Nomoo. ooooo.s Nomoo. oNN omomm. ommoo. wmoNo. moooo. Nomso.N moooo. NNN moomm. mmwoo. Romeo. mmooo. mmNsN.m mmooo. NNN osmom. wamo. moses. mwmoo. _mwoo.m wwmoo. CNN N so .om coo: . m so Eom oposco> oocoossscmsm coch osmogpoozz coch memocpooaI , - . . ol— .: Nah-_J :J_>> ”JOU_1. J)5. .5....i 3 73 H Nmmoo. memm. moNoo. smsoo. NooNN. _Nsoo. mNN mmst. Nwsmo. mmoso. mmmoo. NNmom. mmmoo. mNN N©¢MN. ovsm¢.s mooNo. mommo. «ONON.N oommo. NNN ammos. osmos. NNMNQ. NmNoo. comm—.N NmNoo. NNN wamm. nmsmm. moose. mmsmo. Ommmm.m moqmo. QNN N so N . m so Eom . m so Eom oposco> mocoosssomsm coch osmocpooxz coch osmogpoozz .N .o Aoo..v Nose memos-N ooesce>seo .Nez cos ooosso Nooseoocs cos owes .oN.e o.oos Nvomu vomwo qmmoo. mNooo. mwoom. mNooo. mNN wmwms. mwsom.s moose. vomNo. mmst.s vomNo. omN Nwmmw. omNmo. mommo. mosoo. wmmsm.N mosoo. NNN Nwmmm. vssmo. mmeo. Nmooo. mmmwo.m mmooo. me mwmov. swsmo. mommo. Nsmvo. wsmsm.m msmvo. owN N so m so Eom oposco> ooooossscmsm coch m.mo£pooxz coccm m.wo;pooa: HH 9L .0 «om-_v CPFE WJDD_I_ UJS. .5»...) 5.. .1... 74 H vmmNo. NNomm. NNNoo. mosoo. NmNON. mosoo. mNN mmmoo. mmomm. onoo. Rosco. onwN. Rosco. oNN mNNoN. noses. NONoo. smooo. mmsws.m nmooo. NNN NONwm. oomov. Nosoo. Newso. msooN.m Now—o. NNN Nessa. Nosws. mmmoo. moooo. somo¢.o momoo. owN N so . m so Eom . m so Eom oposco> oocoosssomsm coch msmozpoozz coch osmosuoozz HH .N .o so: fit. BoosN Bocceieo .83 cos Basso 225.8: cos has .8... ozos 75 mmvmm. onos._ VNMNO. N wwowo. poscpmso on sw>m4 kn xwm smooN. ssmmm.s moqmo. N mmmmo. puscpmso on sw>m4 mvsmm. wmsvm. swmso. s swmso. woscpmso on xom wmvsw. NmNmN. Nmmso. N mwsmo. sw>m4 An xwm mNmms. Nmsmw.s osmmo. s msmmo. uoscpmso snowm. mmmnm. omONo. N mmsso. sm>wN mmNso. mmom¢.m momms. s momms. mmw N so N ocoo m mocoo m cosposco> oocoossscmsm coo: so Eom so oocoom HH cooEowNom cos mpoossm pcosuoocs oosssooz cos poms .sm.¢ osoos 76 mmvo. Nvmo. mama. moao. ammo. onac. .>oo .oom coo: Noioooq .Al' . . I 1141!! came. HmuOE mwmmn .oiooo. omeo. osioooN meoo. ooioooN Nsoo. ooiooo. c.No. ooimoo. ooNo. oeieco. iiiiiiiiiiiiiiiiii MM®> >2 moameN MON mum: mocmm2< :mwz cmoo. ~mu05 mmmmn Horoooe ooNo. ooioooa esoo. ooioooa sooo. solosofi oc.o. ooimood oooo. molesoa new» Na moan: Mom Guam wocwmn< cam: oooo. omHo. oooo. mNoo. ommo. Nsoo. mono. NHNo. oemo. ooHo. mofimeoc oomo. omNo. Homo. esoo. moNo. seoo. o.mo. ooao. voNo. oooo. mo.az cofiumHzmom ooeo. ooNo. moNo. oeoo. NoNo. omoo. mmmo. oofio. eomo. oooo. oceoco coc .>oo .oum New: .>oo .oom coo: .>oo .oum coo: 4MMMfldwmm :moz .>uo .oum coo: mmmmm ooiosoq ooissoe MNMMMNM osimso. mNIVNoN xom so ozoo :oNocm cooaopoom cos oooomo< so omopooocoN .Nm.¢ osoos 77 1. Females were absent a greater amount of time than males in September during four of the six years studied. . Females missed more time than did males in September for the six years studied. Males were absent an average of 7.3 per— cent of the time in September, while females were absent an average of 8.1 percent of the time. The researcher feels that there was a significant interaction tween sex and the effect of the treatment in September because the mean >sence for males in 1977-78 was .0074 vs. .0015 for females, and in 978~79 the mean absence for males was 2.6 percent compared to 1.6 percent ior females. The reversal of this trend in 1980-81, where the mean absence rate for males was only 1.1 percent contrasted to 2.4 percent for females, caused a statistically significant interaction with the effect of the treatment to occur. Table 4.33 reveals that there was no significant interaction between sex, level, and district of residence and the effect of the treat- ment in October. The significance level was above a (alpha) = .05 in the case of every variable. Table 4.34 shows that the Significance of F for November was greater than 6 (alpha) = .05 for every variable tested. Therefore, there was no significant interaction between sex, level, and district of residence \nd the effect of the treatment for November. Table 4.35 indicates that there was no significant interaction etween sex, level, and district of residence and the effect of the treat- ent in December. 78 mom . Newmm emm_N. NNNeo w. . mw . N memm. Namo_. mOMNo. N mmemo. “become s mNomw. Nm me_wo. F o_meo. .o a _asas sa xam wwmor. N . mo—wo. HUwmewQ >fi pw>w mmmoe. mmNo N “up; a mmeo. Nowe_. eFNeo. . pave An xom Nmeom. eFQOF. N . F memeF. Fm>w4 an xwm . mrmo Fwovm oomoo. N eomvo. powcpmwo L we u NN—oo. _ NN_oo. _m>m4 oucmowywzmvm mewzcm .m .o mmcmsom xwm new: we Ezm :owpmecm> $0 00L30m HnnHnnHHHnunHnuHHunnnHHuHuuHnHnnHnununnnnnHunnHHnnnnHHnnnnHuHunnnnunnnnnnnnnnnnnnnnnnnnnn :mEpmeH umwmwuoz Low pmwk owrem. mwmvo. mmemm. Nmomm. oommm. ¢N_wx. mwkwc. e we mocmowe_:mwm LQDE®>OZ LOW mpom¥¥m P omNN_. ee__o. N ommme. m_aNo. N omNmo. ommoo. _ meMN._ emcee. N oemmN._ _mmwo. _ emeeN. . N _ .>_ 3.9»: u JID:3 .em.e wreak a An Fo>m4 an xmm memo. wowcpmw mmwmo. powcpmwo >n Fm>m4 ommoo. povepmwm xn xmm FNNQF. _msms xn xam memo. povcpmwo . ~m>m4 ommmo xmm Mme—o. 3b.. 3)...)) 79 «mmum. eopmm. ovowm. wmmom. comm—. mvam. omw—F. , a mo mocmuveecmwm oeNmm. memNo. NmFm . N mNNeo. outcomes an Pw>m4 an xwm _. Nmmoo. N mmmpo. puzpmpn c3 . . Fo>m4 eeo_e mNeNo. _ aNeNo. outcomes s3 xam mwMNm. ¢_¢mo. N aNmeo. _a>as sg xam mea_o.N eFON_. _ e_ON_. auctpmwa oeeee. emeNO. N N_mmo. _a>as N_ewe.N _mNe_. _ _mNe_. xam :owpm Zm> LmQEmuma co» m $0 MULnom we Ezm amok .mm.e opnme c £02 at pomwmm “:mEpmmce no? 80 Table 4.36 illustrates that the Significance of F for January was :er than G (alpha) = .05 for each variable tested. Therefore, there no significant interaction between sex, level, and district of dence and the effect of the treatment for January. Table 4.37 indicates that there was no significant interaction veen sex, leVEW, and district of residence and the effect of the atment in February. Table 4.38 shows that there was a significant interaction between strict of residence and effect of the treatment for March. Significance ’ F for absence by district in March was .01469. This significant nteraction caused the researcher to look at staff absence by district n March in greater detail. Table 4.39 shows the mean percentage of absence and standard devia- tions by district of residence for March for the six years studied. The following conclusions were drawn from the information presented in Table 4.39: 1. Staff members residing inside the Davison School District were absent a greater amount of time than staff members residing outside the district during four of the six years studied. 2. Staff members residing in the Davison district were absent an average of 3.46 percent of the time during March over the six years studied, while staff members residing outside of the district were absent an average of 3.23 percent of the time in March over those six years. 81 mmomm. eoeNN. momNo. N momma. pawtpmwo s3 _aswo an xmm NmmNe. ONmeN. NmaNo. N mmmmp. buwaemaa an _w>ad mmmme. Nmeem. mammo. _ momma. bottomaa an xam mmeNm. OONm_. Nam—o. N NmNNo. _asas an xwm meomm. NmNNN. NNNNO. _ NNNwo. burebm_o omemm. mmeeo. ONeoo. N oemoo. Fa>au eemNN. m_mme._ NONNF. _ NONNF. xwm a do a wee: m mace: m compmrcm> mocmowmvcmwm :mwz go Ezm mo wocaom samseaaa Lea abuaaem peaebmaae emacaeoz toe amok .Nm.4 a_nme MNoom. omwmo. mwmmo. N Fmpmo. povcpmwo >2 Pw>w4 An xwm mwmmN. ommMN._ qvmoo. N mmer. powcpmwo An ~w>w4 waN_. vmmmm.N FFFNF. _ —~_N~. poweumvo An xwm momma. mmwow. mmoNo. N wmpvo. Fw>mA ho xwm MNFNm. #mmoo. omooo. F omooo. purcpmwo omomo. _mwww.N meN_. N NwmmN. ~w>w4 omep. Nnmmp.N mwmor. F mmmop. xwm a we a wee: m .a .9 mega: m coepmwco> wocmowmwcmvm com: to Sam 40 woczom ALGDCMU LOF WJJD. _J J__U_:J.)J.. l). . i 82 mummo. mmNmo. govepmwo kn ~w>w4 >3 xwm mmomm. mMme. N Nvoqw. NNvNF. @0900. N mmmro. purcpmwa an ~w>m4 Fmwa. wwmwm. mmoNo. _ mwONo. powepmwo an xmm mmNom. NvFFN._ mvoqo. N omNmo. ~w>w4 An xwm mmvro. FNQFN.w oprN. — QPNMN. puwgumwo mmwNN. mmoom.— mmmmo. N momrr. ~w>w4 o—me. mmoom.~ _mmmo. _ memo. xwm cowpowcm> m 40 wee: m mace: m wocmowwwcmwm cow: mo Eam mo woczom fizz L8 $805 2958.; BEE: .28 38 .wmé 2E \M;_..«,_k 83 mmmc. mmmm. vwmo. vmmo. wmmo. ammo. ammo. memo. uowuumwa mtflmuso Home. ammo. mmmo. ammo. vmmo. memo. NMNO. wmvo. Como. mmno. ammo. mmmo. wvvo. ammo. ovwo. .>wD .Uum EGGS .>0Q .Uam Ema: .>wo .Uum Amloman mhlmhaa mhlhhma OVMC. :MUE MPCN. Nauoe mmmm4 genomes oemo. asumeafi same. we-s>aa ammo. sN-oBmN memo. asimsaa ammo. melesmm uvfluumflm wCNm:H wmmo. homo. mvmo. cow: mcmoz mo mQNumEESm Name. mwmo. wamo. meo. mhvo. Ammo. .>@D .fium :mwz MmuesaN uoquumfla wave. demo. Name. Name. meamuzo uofiuumwo moqo. memo. move. same. meamcp cofiumHJQOQ ONvo. ammo. ceqo. osmo. ouaucm pom .>aa .Cum cam: .>wo .eum :mwz Na>aq meumsmN msiqsmfi .mm.¢ wFQmH powcpmwo Na czom coxocm cos: seem: Lo+ oucwmn< wo wmwpcwocmm 84 The researcher believes that the reason for a significant inter— on between district of residence and effect of the treatment for :h was that the mean absence rate in March dropped from 3.70 percent 1974—75 to 2.83 percent during 1980-81. Table 4.40 illustrates a significant interaction between level and ) effect of the treatment for April. Significance of F for absence level in April was .04593. The researcher investigated staff absence ’ level 1“ ADril as a result of this interaction. Table 4.41 indicates the mean percentage of absence and standard \EViatlons by level in April for the six years studied. These conclu— Slons were derived from the information presented in Table 4.41: 1. Elementary teachers missed the greatest amount of time in APril during four of the six years studied and second most the other two years. 2. Junior high school teachers were absent the greatest amount of time in April during two of the six years Studied, the second greatest amount of time during one year, and missed the least amount of time during three of the years. 3. High school staff members missed the second greatest amount of time in April during three of the six years studied and the least amount of time for the other three years. A compilation of the means shown in Table 4.41 is illustrated in Table 4.42. Elementary teachers were absent an average of 3.48 percent of the time in April for the six years studied. Junior high School staff members were absent 2.85 percent of the time, and high h 01 staff members were absent 2.49 percent of the time, 3C0 85 mvmom. . . mmmoo F ommmo N ammFF. HQTmewo an Fw>w4 xn xom eummo. mmmpw.N FNmmr. N Neemm. powepmwn An Fm>m4 waom. mm_4e. eNeNo. _ eNeNo. sattsa_s ss xam NmmN_. 4NN_N._ N_No_. N eNVON. _a>as as xam mmqno. oeNmN.m QNNNP. _ oemmF. “uptempo mmmwmq NNNm_.m moomp.. N N_owm. _a>as . xw NN_NN. eNNNN._ _ MNNNO coppmmtaw mo Ezm mo.mos:om a do mocmu_e_cmvm .o¢.a break 2 Lonv vwmk FFLQ< com mpummmm nemEpmmLF ememwco 86 memo. .NNo. NNeo. mesa. ence. NNNo. Neqo. some. 111111111 .>oo .mum cam: mmvomma X mama. ONNo. name. Name. ammo. omao. came. mmvo. News. «one. ammo. NNeo. name. Mmmo. memo. memo. 111111111 1111 111111111 .>oo .wum :moz .>oo .wum :mmz NN1QPNN ep1esma 1111111111111111111111111111111111111 wage. emNo. .mmNo. mafia. Nose. «vac. memo. mNmo. anm .eum new: Ne1aaae _m>m4 An egos :mNocm ems: Mth. memo. mmmo. mhmc. meqo. mama. mmmo. mmNo. 1|Ill|1|l .>®D .Cuw :60: ll‘lulIIIIl omeo. esNo. Nmeo. ooNo. «Nee. come. «Nee. mNNo. 111111111 .>oo .eum :mmz 1111111 es1mhma \‘l‘u Fecu< cw mucmmn< to owe vcmoemm aoozum 5mm: uoflcmm Hoozum 56H: nodcsh humacwfiwam coflumasmOm wuwucm Mom H®>®A .~¢.¢ mPDMP 87 memo. mwNo. memo. moe_. o_NF. cam: mmoN. _mpop _NNo. . . moeo NNmo me_1ommN OFNo. om_o. eomo. mm1mnmN NmNo. mNeo. mNeo. wN1NNQF mmNo. me_o. eeeo. NN1on_ mmNo. ooNon oomo. m51mnm~ . emNo. ms1enm_ moNo. NNNO mm: mm : apex mucmmn< 2mm: mpmm mommemmEmFm mpmm mucmmn< :mmz _ooeum ;N_I Loeeam Nooeam est: ao_ess Fceee=m .Ne.e argue :mxoem ems: Fgcq< :N muemmn< com memo: mo mm. m>mN An czoo . me> new _ r7 88 ' 1 an interaction between leve The researcher feels that there was bsence for and effect of the treatment in April because the mean a ers during 1980—81 was 4.69 percent com- junior high school staff memb pared to 2.5 percent for the first five years studied. Table 4.43 reveals that there was no significant interaction between sex, level, and district of residence and the effect of the treatment in May. Table 4.44 shows that there was no significant interaction in June between sex, level, and district of residence and the effect of the treatment. The significance level was above a (alpha) = .05 for every variable tested. Months of the Year, Test for Interaction Between Age and Treatment Univariate F-Tests were also used to test for interaction between age and treatment by months of the year. The Significance of F for the percentage of absence for 1980-81 (P80) as compared to the composite percentage of absence for 1974-75 to 1978-79 indicated whether or not there was a significant interaction between age and the treatment for the particular day being tested. The significance level at which these tests were conducted was set at a (alpha) - .05. Table 4.45 shows that the Significance of F for September was .51914. Therefore, there was no significant relationship between age and the effect of the treatment for September. There was no significant relationship between age and the effect of the treatment for October. The Significance of F for October was .13692. This information is summarized in Table 4.46. 89 Nman. ¢MMNN. emcFo. N nmwNo. poFcmeo >2 Fm>m4 ma xmm momma. emeum. mmmFo. N memo. qucmeo za Fm>m4 mmemo. FmFON. mmoFo. F mmoFo. FuFmeFa an xmm mmmmm. mommo. ONmmo. N cameo. Fm>m4 ha xmm Fomwe. «mev. mmmNo. F mmmNo. poFcmeo NNme. NmNNm. mmNNo. N wmmmo. Fm>w4 ONmmm. mchm. meFo. F meFo. xwm a we a mcmsam .u .Q mmcwzcm :onchm> wucmoFFchFm :mmz Fo Ezm Fo moczom mesa LOF mpuwFFm “swapmmLF vaFFuoz LOF meF .¢¢.¢ anmF ewFom. mmweF. ommoo. N FomFo. qucumFo an Fm>m4 an xmm MNmmn. memNN. wmmoo. N mmmFo. poFLFmFo An Fm>m4 mmmmm. evooo. Noooo. F Noooo. poFcumFo Na xwm mFFNm. mNmNo. wNFoo. N mmNoo. Fw>m4 an xmm «NNmm. mmnmm. mmmmo. F nmmmo. poFcmeo eemNo. mnmoe. N¢ONo. N mmoeo. Fm>m4 Fooom. mmqmo.F Nmmeo. F Nquo. xwm a Fe m wcmzcm .d .o mwcmzcm :oFFchm> mocwoFFchFm cam: mo 53m $0 woczom wmomw. emNmo. mmvoo. mFmFo. mm; mmon. waoo. mmmoo. mnmoo. mNa mFva. momma. Nommo. FmNNo. mm; mNoeN. emmmm.F ommmo. ommNF. mm; NaomF. FmNmN.N woemo. mNomF. owe a to a eacasam a aFanFsz apcha> mucmuFFchFm :mmz coccm .m .o Fom.Fv chz mmeF1m muchm>Fcz .Lwnopuo LOF FCmEpmwcF vcm mmq :mmzpmm :oF bomcmpeN toe pmaF .ee.e aFeeF O 9 FmFNF. mmmmw.F eONoo. eNmeF. mNa mNomo. mNmmF. FmNoo. mONeo. eNa mNmNe. Feoep. oemoo. wFNeo. NNa oaeNo. FNNON.m NNNmo. mNMMN. wNa «FmFm. amer. emFNo. cameo. owe a to a emcasam N aFanFsz mpach> wocmoFFchFm cam: Loecm 91 W5 '7 4.47 ~ . , of 6222. 1ndlcates that the Significance betwee 'her hlp efOr 'onS and e, there is no significant relatl effect Ther 0f the treatment for November- 3 th Was . . . . n age 0f the no Slgn1f1cant relatiOnshlP betwee for December '87234 m9nt for December. The Significance Of F ‘Th’- , 1S ‘nfOrmation is summarized in Table 4°48' .01347 Tab ary was le 4'49 Shows that the Significance of F for Jan” f° . his ‘ndlcate age and . . etween S that there was a significant relationshlP b . ion e effect of the treatment in January. A more detailed investigat ~ percentage 0f absence in January when broken down by age group 15 hown in Table 4.50 and 4.51. Table 4~50 illustrates the mean percentage of absence and Standard eVlations for January by age groupings during the six years StUdied' ible 4.51 summarizes the means of absence for January for various age “0UPS. Davison staff members in their twenties missed the greatest lount of time, an average of 6.15 percent. Staff members in their fties missed the second greatest amount of time during January, 5.01 rcent. Teachers in their thirties were absent an average of 3.29 per- nt of the time; those in their forties 3.05 percent, and those staff nbers in their sixties missed only 1.81 percent of the time for sence during Januarys. The researcher believes that a statistically significant inter- :ion between age and the effect of the treatment appeared because re were zero absences during the 1980-81 school year for Staff bers studied who were in their sixties. 92 mmomm. oooww. mmeoo. eemmo. mNN NONoO. mmoFm.m eeNFo. emmm_. eNN momma. ooooo. eFmNo. _oooo. NNN Fmoon. NNNeF. Nono. Nmoeo. NNN NNNNN. NNmNo. Neemo. NmeFo. CNN N to N eacmsam N aFNFstz apcha> wocmoFFchFm :mwz Loccm .N .N Aom.Fv NFF3 mwmwF1N mmecm>Fcz .cwaemoma LOF “:webmmcF use mm< :mwzpmm :onumcmch LOF pmmF .w¢.¢ anmF mmmFF. NFFNm.N NNFOO. momeF. mNN eo_eN. momma. meNoo. eFNmo. eNN NmmN_. mFeNm.N NFNNo. NmooF. NmN eNNmo. NNNQN.N mFNeo. NNNNF. NNN NNNeN. QNNmo. QNFQN. NmFmo. omN d to N emcesam N aFNFbFsz apaFae> moemomeszm 2mm: cocem 93 Ommmw. ommmF. momoo. mmFeo. mNN NmeF. mmNFm.N NmmFo. memF. oNN mmewF. onmwN.F NmNeo. emmmF. NNN NvaN. mmwFF. mmmmo. NNomo. wNN NemFo. mmemm.o mNFmo. owomN. owa N .6 N .2293 N «3.53: 33.54, mocmoFFFszm cam: Loccm .N .o Fom.Fv chz mummF1m muchmcha .xgmzcmw com “:mEmecF new mm< :mmzpwm :onomcmucF LOF pmme .md.¢ anwk 94 I!!! o o o ammo. o o o o o come. 0 o me1oe mom< mmHH. th0. Memo. mHHo. NNmo. mmmo. mmmo. memo. mo¢o. oomo. omho. omho. mmlom mmm< wove. mmvo. memo. mmNo. ammo. meo. mmeo. ammo. Nova. NNNo. move. ammo. oe1ov mom< ammo. Homo. vmmc. ¢mao. ammo. Hmvo. move. ammo. omvo. memo. homo. hmvo. ¢m1om mama Home. Nvmo. o o vmwo. mmmo. ommo. hmmm. o 0 undo. memo. mmtom mwm< COHumasmom NSC. Ammo. ohmo. come. ammo. Fovo. memo. mmmo. mmvo. demo. oomo. :vo. oufiucm pom Soc .Bm com: .>wo .Foum. :mwz .>mo .95 com: JNMMJWMW. com: 500 .oum new: See .Fuum new: W13 Mmummmm mmummmm .mmummmm anmmmm mmnmmmm ms1vemF .om.¢ anmH masocw mm< xn egos :mNocm ems: xcmscmw NOF mocmmn< Fo wmmpcmoch 95 FoFo. Fomo. momo. oNoo. mFoo. cam: mwoF. woom. onF. NNoF. omom. FopOF o NNNo. oNeo. FoNo. Nomo. Fo1oooF oooo. oFFo. ooNo. ooFo. o oN1oNoF o mmNo. Fomo. Fmoo. mNNo. NN1NNNF oomo. oomo. NmNo. FoNo. NNNN. NN1oNoF o oooo. FNNo. momo. o oN1mNoF o ooNo. Nomo. NNoo. mNmo. mN-oNoF me> uFo mcom> mo1oo oFo meaNN om-om oFo acaaF N41oo oFo meaQF om1om oFo mamaF NN1oN mcmnEmz FFowm LOF mocmmo< Fo mmoucmocma com: mooocw mm< an czoa :oNocm can: xcoocoo LOF mocmmo< Fo mchoEEom .Fm.¢ anoe 96 There was no significant interaction between age and the treat- for February. The Significance of F for February was .89309. 1 information is summarized in Table 4.52. Table 4.53 shows that the Significance of F for March was .36545. cefore, there is no significant interaction between age and the act of the treatment in March. Table 4.54 illustrates that the Significance of F for April was 215. There is no significant relationship between age and the 'ect of the treatment in April. There was no significant interaction between age and the treatment * May. The Significance of F for May was .31303. This information summarized in Table 4.55.. Table 4.56 indicates that the Significance of F for June was .61277. re is no significant interaction between age and the effect of the atment in June. sons for Absence, Tests for Treatment Univariate F-Tests with (1.90) D. F. were utilized once again to for significant treatment effects for each type of absence. The ificance of F for the percentage of absence for 1980-81 (P80) as ared to the composite percentage of absence for 1974-75 to 1978-79 cated whether or not there was a significant treatment effect for particular reason for absence. The significance level at which e tests were conducted was set at a (alpha) = .05. 7 9 momoo. wFNoF. mmm NwNmm. mwmwm. mmmmm. Nvmmo. NrmFo. FmNmo. wk; mmFmo. NmmNm.m memo. mmwa. mma momwv. omvmv. momma. mmeo. mum wwwwm4 mvaw. ommmo. mvmmo. own N .8 N 8.23 m N 2 .53: BEN; muzmoFchmFm cow: Loeem l7) .N .o Aom.Fv cpwz mommF1m mumFNmch: .cocoz Low #cmEpowNH Uco wmq :wame :onoocmwcF NOF pmwh .mm.¢ anoF memm.v wNmoo. NmmFN. mm; mmmmo. mmmvm. meoF. FmFFo. mnemo. mm; NNNmm. mwNoo. mmmNo. mmmoo. mum QNmmm. vaFF. memoo. Fommo. wma mommm. meFo. moFoF. FNvFo. owa N as N out: m N 2 .53: SSE, meteoNthmFm :mwz Loecm 77 8 9 IlI1II11I1II1I1II1I1I1l11lIlIIIIIIIIIIlI1lII111IIII1llIlI1II11111111111I1111111111I1 Fommm. quoo. mnemo. mmm mmm mmvmm. vomvo. ammON. mmoFo. NNwwo. mmNmN. momoF.F quNo. «FmFF. momNm. meMN. NMMNO. moFmo. wmwmmd NmmNo.F moovo. omooF. coco: m m wF Fszz A F0 L mozmoFFFszm cow: Loccm .N .o Fem.Fv cpwz puonFCF com pmwF mum mum 0mm mpoFNo> .mm.v anoH mumwF1N mquLm>Fcz .ooz com pcpromNe vco mm< cwame :oF FmoeF. emmoo. Nmmmo. mNN oNN mmmom. mmmvw. Fvva.F mmwFo. wFFNF. MQOKQ. mmFQo. mommo. mmmoo. wwmwm. mmmFN. mmeo. omwwo. mkmkm. mveom. MVNmo. Nmeo. x wF Fszz coco: m Rpm mum ow; mpoFNo> 4 mo N motmonmcmFm com: Loccm 9 g NNeNo. oNNNo. NNNoo. ooooo. oNN NNooo. ooNNm. oNooo. oooNo. oNN NoNNN. ooooo. NoNoo. mooNo. NNN momma. oFeom. NoFoo. NmNNo. NNN NNMNmn. oonN. ooooo. oommo. oNN 1... Lo N coco: m mocmoCchFm com: (Sim nnnnnunnnnnnnnnunnnnnnnnnnnnnnnnunnnnnnnnnnnnnnnnuunnnnnnnnnuHnnnnnnHnnnnnunnnnnnnnnnnnnnnnnnnnnn .n_ .o Aomév £sz 33.th 33.23:: .955 (SF Newsweek _oco mm< 235% 233235 .EF 33 .86 335 N NF FpFoz wanNa> lOO Nurses: The test for treatment effect upon absence for illness is illus— trated in Table 4.57. The Significance of F for this test was .74505, There was no significant treatment effect on absence for illness. Personal Leave The test for treatment effect upon absence for personal leave is depicted in Table 4.58. The Significance of F for this test was .47421. There was no significant treatment effect upon absence for personal leave. Wis The test for treatment effect upon absence for school business is shown in Table 4.59. The Significance of F for this test was .22379. There was no significant treatment effect upon absence for school business. Dock Days The test for treatment effect upon absence for dock days is illustrated in Table 4.60. The Significance of F for this test was .59878. There was no significant treatment effect upon absence for jock days. Bereavement The test for treatment effect upon absence for bereavement leave ‘5 shown in Table 4.61. The Significance of F for this test was 5737] There was no significant treatment effect upon absence for 1ereavement leave. lOl 7 mmmFF. ooNNm.N Noooo. ooooo. NFNoo. moooo. mNN omqu. onomN.F Noooo. moooo. momoo. woooo. mNN qNNNm. NVOmo. wFooo. Foooo. quFo. Foooo. NNN mmwoo. Nmmo¢.w mNooo. FFNoo. quNo. FFNoo. wNN % $.29 Sooo. NNooo. Fmomo. NNooo. as N No N . m cow: .Um Fo Ezm . w No Eom mFoFNo> mocooFNchFm Noecm mmespoa>I NONNN mmecpoozz X/// .N .o Fom.Fv 59F; mamme1N mpoFNo>Fcz .w>om4 Fo:OmeN cow mucwmn< co powNFN pCmEpowee Now pmwe .mm.¢ anoF X/ Nvomc. NmmNm. mNooo. . NFooo. mmomo. NFooo. mmN ¢m©mN. FmFoF.F Foroo. NFFoo. vNFmo. NFFoo. ©NN mNmmo. wmme.¢ FmNoo. oFmFo. OONmN. oFmFo. mum memm. momFm. mFmoo. FmFoo. #mmmw. FmFoo. mna women. ammoF. momoo. omooo. vaFm. mmooo. owN N No . m :owz . w No Eom wpoFco> wocooFFchFm NOLLN mmeLFONNr LONLN mmespoozz .N .o 89: CHIS mHmv_lL Don: _U>_:D .77)....1 .1. 102 1111111111111111111111111111111111111111111111111111111111111111111111111111111 mmNNm. meoMNo. Noooo. ooooo. omFoo. ooooo. mNN wmmom. moNFo. FFooo. ooooo. omooo. ooooo. mNN NFvem. vmvoo. oFooo. ooooo. mNmoo. ooooo. NNN mmNNw. NNMNO. moooo. ooooo. omNoo. ooooo. mNN mmmmm. meNN. oFooo. voooo. omNFo. ooooo. owN N No N . m com: . m No Eom . m No Eom mpoFNo> mocooFNFcoFm Noccm mmeLFoozI NONNN mmecpooxr nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnHnnnnnnnnnnnnnnnnnnnnunnnnnnnnnnnnnnnnnnnnnnn .N .o Noo.: chz mpmwF1N wpoFLo>Fcz .mooo Noam LON mocmmn< :o powFFN “:mEFowNH cow pmmF .oo.¢ anoH 11111111111111111111111111111111111111111111111111111111111111111111111111111 omNow. mmoFo. woooo. . ooooo. mmmoo. ooooo. mNN NONON. ommFo.F NFooo. ONooo. moFFo. oNooo. mNN mmNom. mmFmo. mmooo. moooo. mFFmo. moooo. NNN omNom. «mmoF. wFFoo. NFooo. omooF. mFooo. mmN NNMMMN oooom.F mmooo. Noooo. meooo. Noooo. ooN w wo . m :mmz . m cow: . m %0 Sam . m we Ezm wpmem> wocooFFchFm NONLN mmeNFoozI NONNN mmecponzz (I .N .3 \DhiF :J—z 0)0).. . Ir)’. .(ry...1 103 "\-l I/i mmwwm. vammN. ooooo. Foooo. Nmmoo. Foooo. mNN mmNmm. mNmmw. moooo. moooo. mmmoo. moooo. mNN aomoo. mqmmN.w mNooo. MONoo. mFNNo. moNoo. NNN mmnFm. woFmF. mmooo. Noooo. mowoo. moooo. wNN flue. ooot. omooo. ooooo. NNNmo. ooooo. ooN “— Nb N . m cme .Um Nb Esm . m Nb Ezm wpmem> wucouFFchFm NONNN mmeLFoazz LONLN mmezuoazz /I// .N .o Aom.FV :sz mpmwk1N mpoFco>ch :mEpowce LON umwe .Fm.¢ anoH .w>oo4 pom5m>owcmm NON mucwmo< co pumFNN u 104 .QQXiEQDNEQEEEtion Association Busifléii E A. buSineS r D. ° The test for treatment effect upon absence f0 65 5 test W ° - hi 13 depicted in Table 4.62. The Significance of F for t r t upon absence f0 .30496. There was no significant treatment effec 3aVison Education Association business. m . t 15 lllUS" The test for treatment effect upon absence for Jury d” y . .16078. :rated in Table 4.63. The Significance of F for this test was 'here was no significant treatment effect upon absence for jury duty. figspns for Absence, Modified Treatment fleets Analysis of variance was used once again to test for modified reatment effects or interactions between sex, level, and district of esidence and treatment. The significance level at which these tests ere conducted was set at a (alpha) = .05. Illness Table 4.64 illustrates that the Significance of F for absence )r illness was greater than a (alpha) = .05 for each variable tested. 1ere was no significant interaction between sex, level, and district i residence and the effect of the treatment on absence for illness. Personal Leave Table 4.65 indicates that there was no significant interaction itween sex, level, and district of residence and the effect of the eatment on absence for personal leave. 105 rewow. oomwm.F 50000. @0000. oFmoo. moooo. mNN Noqu. mommm.F moooo. moooo. oFmoo. moooo. mNN NNOON. FoFoo.F moooo. NFooo. vmmoo. NFooo. NNN FoNON. omomN.F Noooo. moooo. qFooo. moooo. mNN wnooF. ohmmm.F Noooo. omFoo. NFooo. vaoo. owN N No N wcm com: .cm cow: .om Fo Eom .om Fo Eom wquNo> mocmoFFchFm soccm mmezpooA: NONNN mmecpooxz .N .o 8?: 59F; mummH1N mpoFNo>Fco .xpoo acoo NON mucmmo< co pomFFN “:mEpomNH NON pmmF .mm.¢ anoe momma. mowwm.¢ ooooo. ooooo. moooo. ooooo. mNN ooNoF. mooom.N ooooo. ooooo. oFooo. ooooo. oNN mFomm. Noooo. Noooo. ooooo. meoo. ooooo. NNN NmoFN. mmmvm.F Foooo. Noooo. mmooo. Noooo. wNN omqom. N¢¢©Q.F voooo. ooooo. NFmoo. ooooo. owN N No N .om com: .om com: .om No Eom .om No Eom mpoFco> mozooFNFcoFm NONNN mmecpooxr NONNN mmecpoozz ammVN. wmoN¢.F coooo. N oNFoo. poFLomFo so _a>mo so xmm omome. ONoow. mmooo. N Nuooo. poFLFmFo mp Fm>m4 mwvon. movoF. @0000. F @0000. FoFNmeo an xmm mFoom. qumm. mFooo. N Nmooo. Fm>w4 on xmm Fmomm. momow. wmooo. F wmooo. quLNmFo w¢NNm. oooom. oNooo. N wmooo. Fm>m4 mmNmm. Neme. mFooo. F mFooo. xwm N Fo N wcoovm .N .o mmcooom :oFFoFNo> mucooFFchFm one: No Eom mo wocoom m>om4 FocomcmN NON mucmmn< co mpomFFN pcmEpomee vaFFvoz coF pmwp .mo.o anoe "w meFo. MNooo._ owooo. N mNFoo. quNmeo he Fm>m4 on xwm NNooo. ooNNF. NFFoo. N omNoo. ooFameo so Fw>ao Foowm. oNooo. ooooo. F ooooo. FuFNmeo he xwm mmNmo. FmeN. womoo. N mowFo. Fm>w4 an xmm ONmmm. ooFNm. ommoo. F ommoo. poFcmeo mNFNm. mNNom. ammoo. N .NNoFo. Fw>m4 mmooF. mmoNo.F mmmFo. F ommFo. xwm N No N mcooom .N .o mmcoocm :onoFco> oocooFFchFm com: No sow Fo wocoom IIIIIIIIIIIIIIIIIIIIIIIIllllIlI-----—-———~ 107 School Business Table 4.66 shows that the Significance of F for absence for school business was greater than a (alpha) = .05 for each variable tested. There was no significant interaction between sex, level, and district )f residence and the effect of the treatment on absence for school )usiness. Dock Days Table 4.67 depicts that the Significance of F for absence for lock days was greater than a (alpha) = .05 for each variable tested. 'here was no significant interaction between sex, level, and district f residence and the effect of the treatment on absence for dock days. Bereavement Table 4.68 shows that there was no significant interaction between 3x, level, and district of residence and the effect of the treatment 1 absence for bereavement leave. Davison Education Association Business Table 4.69 indicates that there was a significant interaction etween sex and the effect of the treatment for D. E. A. business. gnificance of F for absence for D. E. A. business by sex was .04635. is significant interaction caused the researcher to look at staff sence by sex for D. E. A. business in greater depth. Table 4.70 shows the mean percentage of absence and standard devia— Jn by sex for D. E. A. business during the six years studied. The llowing conclusions were drawn from the information presented in )19 4.70: 108 omooo. Nooom. Noooo. N «Fooo. FuFNmeo An Fm>w4 An xmm ooNoF. Foomo.F oNooo. N omooo. antomFo so Fmsao Naomm. Fmooo. ooooo. F ooooo. FoFNmeo An xmm NNNNo. oNooo. Foooo. N Noooo. Fm>mo so xmm wooFm. FmFoo.F mFooo. F mFooo. poFNmeo mvam. Nmeo. Foooo. N Noooo. Fm>m4 emmmm. Nmmem. moooo. F moooo. xwm N No N mcooom .N .o mmcooon :onoFNo> mocooFNFcoFm com: me Eom No mocoom mxoo Nooo NON mucmma< co muomNNN pomEpowNF omFNFooz NON pmwF .Nm.o mFooF oommo. ooooN. moooo. . N moooo. quNomFo so _m>mo so xam vamN. mNNmm.F mmooo. N moFoo. quNumFo an Fm>mN momma. mmmwN.N ooFoo. F moFoo. FchumFo on xmm mommm. NNNFF.F omooo. N mFFoo. Fm>m4 An xmm ommmo. moqmo.m NmFoo. F NoFoo. ochumFo Nommq. omomm. vqooo. N mwooo. Fm>m4 oNNom. NmFmF. woooo. F woooo. xmm N No N mcooom .N .o mmcoocm coFooFNo> mocooFNchFm now: No Eom No mocoom 109 mm00m. «Fowo. Noooo. N ooooo. 8.23.5 3 F93 3 saw NFFNN. omooNF moooo. F ooooo. 8:55 3 F23 Naomi oooFF. ooooo. F ooooo. 8:35 3 pm Room. oNoNo. Noooo. N moooo. F33 so am ooooN. NmoF F . F ooooo. F Noooo. 8 E3 .5 Na FoF. ooFoo. F Foooo. N o 88. FEB g oooooo 289 F mFooo. x13 1.— ...F0 11— wLmzcm .N .D mmLMJUm Cesar—“5 wocooFFchFm cow: No Eom No mucoom mmmcszm :onoFoomm< :oFuooovN comF>oo NON wocmmn< co muomFFN pcmEpomNF umFNFuoz New Home .mo.¢ anoF vaNm. NNmNm. NFooo. N vNooo. poFNumFo An Fw>w4 An xwm memm. ooomN. oFooo. N ONooo. poFNmeo An Fw>w4 ¢v©wN. NoFmF.F mvooo. F mwooo. quLumFo an xwm #mmmm. mMNmm. NNooo. N veooo. Fw>m4 An xwm NMNNm. mmva. @0000. F @0000. uuFmeFo vNFom. mmmwv. “Fooo. N mmooo. Fm>w4 vwnom. eoFoo. 00000. F 00000. xwm N No N wcooom .N .o mmcooom :oFFoFNo> mucooFFchFm com: No Eom No wocoom 110 oooo. Fooo. a o oooo. Fooo. n>oo .cpm coo: Fo1oooF a v .>oo Hoe. Fmo. .Uum mulmnmm o vooo. Nooo. coo: xww X0 5303 :wxoLD :D:: nnDZFGSD m m Noco Hoe Hooo. o o o. O. wamsoh o woo. woo. >00 .Oum mhIhhmH o mooo. mooo. :mwz II If! I I!!! 9900. mooc. mocc. Hooo. mooo. .oFa: h m .>00 0 Foo. Foo. .flam :eoz mFguOE Hm1owma mhlmhaa m>1nhma hnlmhmm ¢>1m>ma m>1chmF o o mooo. mooo. Nooo. wooo. 8% 5.2. .Bm whiwnma o Hooo. Hooo. coo: onlmnma nr~ pl. 05. .>. o mace. NHoo. .>oo .oum mulvnmfi o mHmeN mooo. mam: :ofiuszmom woos. oufiucm pom coo: mmzouo 111 l. Males used more time for D. E. A. business than did females during the six years studied, even though total absence for this purpose was minimal. 2. The reason that there was a significant interaction between sex and the effect of the treatment for absence for D. E. A. business was that females studied used leave time for D. E. A. business in 1980—81, where only males studied had been absent for that purpose during the first five years studied. Jury Duty Table 4.71 illustrates that the Significance of F for jury duty greater than a (alpha) = .05 for each variable tested. There was ignificant interaction between sex, level, and district of residence :he effect of the treatment on absence for jury duty. 1ns for Absence, Tests for Interaction Ten Age and Treatment Univariate F-Tests were employed again to test for interaction en age and treatment for reasons for absence. The Significance of the percentage of absence for 1980-81 (P80) as compared to the site percentage of absence for 1974-75 to 1978-79 indicated whether i there was a significant interaction between age and the treatment 1e Particular reason for absence being tested. The significance at which these tests were conducted was set at a (alpha) - -05- 112 NONNm. FFFNF. ooooo. N oFooo. FchFmFo so Fa>ao so xam ooNFo. Fmme. ooooo. N ONFoo. FUFFFmFo an Fm>w4 memmm. mFemN. oFooo. F oFooo. poFNmeo an xmm ovaN. mmwFo.F noooo. N omFoo. Fm>m4 an xmm mNMNF. NFeNe.N moFoo. F moFoo. poFcpro mmmmw. onmF. oFooo. N oFooo. Fw>m4 mamme. vmomv. mmooo. F mmooo. xmm N No N mcoocm .N .a mmeooom :oFFoFco> moewowNFemFm com: me Eom No mucoom 33 5.3. NON 83?? :o muomtm 295$: umFFFuoz NON meF .Fmé mFooF 113 “1% Tab 1e 4 7 l] ‘ 2 Sh he OWS t e Dd 38 was ~81022 hat the S1.gnlficance of F for staff absenC . n effe p Ct 0f the e rsona] Leave The r a t 1 treatment for absence for illness- cant relationship between age and the effECt reatment 2or t on staff absence for personal leave. The Significance S aff ' absence for personal leave was .45654. This informc’itlilon ”Strated in Table 4.73. EEJEKXLJtezutee: Table 4.74 shows that the Significance of F for staff absence for business was .40311. .There was no significant interaction between d the effect of the treatment for absence for school business. Dock Days There was no significant relationship between age and the effect treatment on staff absence for dock days. The Significance of F 1ff absence for dock days was .84687. This information is summar- 1 Table 4.75. greavement Leave ‘able 4.76 illustrates that the Significance of F for staff for bereavement leave was .86108. There was no significant tion between age and the effect of the treatment for absence for nent leave. gyison Education Association Business 1ere was no significant relationship between age and the effect :reatment on staff absence for D. E. A. business. The Significance ll4 ¢a©rm. mmPoN.N Noooo. ©m©m_. mum moomr. mmooo.m Rocco. Rene_. we; wmewe. “_mno. m_ooo. ammmo. “Na Nmeoo. “meme.“ mmooo. N_QNN. wee «meme. m_mmm. eeooo. wmmeo. owe a ea a emeezam a w_ave_=z apewee> mucmuwmwcmwm new: Loeem a .a Aom._v sew; mbmme-e wpeeee>wez .w>eme _m20mewm Low wocmma< mmmum Low pcmspmwgk new wm< :wmzpmm cowuuwgmch Low “map .mm.¢ mpnmh 035mm. mwmmm. mwooo. memo_. mma mo~m_. mmmmn._ _o_oo. emmm_. one Raves. Nmmem.m _mmoo. mmmwp. “ma emmmm. Ne_m_. m_moo. o_o¢o. wee mmofim. _ommo. momoo. wmmmo. owe .e.eo e emeezem a apawe_:z mpe_ee> mocmuwkmcmfim :mwz Loegm llS Ommoo. mrwww. Noooo. wmmwo. mum waom. emmyo. _Pooo. “_N_o. wee «memo. wmmoo. o_ooo. memoo. “Na doom“. ”memo. moooo. «memo. we; emmew. _mmmo. e_ooo. Peomo. owe a +0 a emeeaem a mFawp_=z mpewee> wocwowwwcmwm :mmz Loggm .e .Q Aom._v sew; mpmme-a apewee>wcs .mseo Moog L04 muzmmn< mmmpm Lem psoEummLF use wm< :mmzumm corpomemch Lee pmme .mm.¢ whame eoomm. mmmem. woooo. Nmmmo. mm; mmmmm. mmm_w._ NFQOO. memp. on; mmvmx. «memo. mmooo. wmwmo. nun mvmmx. fimpmo. mFFoo. «mpmo. mum -mow. mmmom. mmooo. owwmo. own A to e emeezem a a_awu_:z auewee> untamemmcmxm new: Loegm ll6 mmwrm. Fmomr. voooo. mommp. mum mmmwm. mmmmm._ moooo. ANNNF. on; ommoo. m¢mwo.m mmooo. mFQNN. mum mcvmo. mNmNo. mmooo. mm©~o. mum wofimm. owomo. omooo. omwpo. own a e0 a . emeasem e mpawp_=z meewee> mucmowmwcmhm new: Loegm .e .Q «om.hv new; mpmwe-e mee_ee>w:: Lem mocmwaq m mmum com “:maummgp Uzm mm< :wmzumm co .w>mw4 pawsw>mwgmm wpomewch so» pmw» .om.¢ wpnmh T . n 0f t here was no significant interaction betwee he treatment for absence for jury dutY- W al 3‘ y ls of variance was us n l . 9d to test for effects of sex, 19V913 Stri Ct of r ' eSldence on average absenteeism by days of the week, ‘ 0f the year, and by reason for absence. The significance level c h these tests were conducted was set at a (alpha) = ~05. Lewes Table 4.79 shows that there was significant interaction between district and absence time taken on Mondays. The researcher ed additional statistical information on staff absence by sex by :t of residence for Mondays. This data is presented in Tables 4.8l, and 4.82. The following conclusions were drawn from the . Staff members who live outside the Davison district miss more time for absence (3.46 percent) than do staff members who live inside the district (3.28 percent). . Male staff members who live inside the district miss more time for absenteeism on Mondays (3.06 percent) than do male staff members who live outside of the district (2.07 percent). 118 owwwr. ommmw._ Rocco. mmmefi. mm; emwer. ommmw.P “coco. mmme_. wee mmom_. mmeo_.m Rocco. m__m_. Rea omemr. emomu.~ Rocco. memm_. wee mmmFN. emmmm._ Rocco. __am_. owe a go a emeezem a a_mep_=z weewee> mocmowemcmwm cow: Loggm .d .o “om.fiv sew: mpmme-d mpewee>wes 5:5 \Cams (5% wocmmflx quHm Lo; “:wEumeH bcm mm< :mwzfiwm coquMLmucH Louv pmwh .wmé 2.an memes. “meek.m ooooo. m_eem. meg emmme. mmmmm.m cocoa. cummP. we; emeom. ommho. Noose. mmmro. Rea Ream. Seem ; :58. m8 _ F. m: “Aemmw. oemom._ eoooo. mmeP. owe n\.xo d emeezem m m_awp_=z apewee> mfixsmuwkxeaiun :mwz Loeem Hg 29:. womomd mmemo. m 03.8. 3.:me 3 33.. B xmm ENE. mmmmm; Sumo. N 830. ”6.7.3.5 3 7:3 938. flowed meo. _ meo. 5.:me E xmm mmmmm. mmmom. 038. N 880. $33 3 xmm mmwmm . momma. mice . _ wq So. 5me.5 memes. mmmmm.m momma. _ memmo. ANV _w>w4 mmmmm. Nvmg. mmooo. _ muooo. CV P93 mmmdb . new: .m ~82 . F Som F . xmm .m.xo .& mcmzcm .d .Q mwgmzcm :owpmwgm> mbtmutxtmxm. 2mm: 08 52m 08 8.58 l'll( Wxfipbtoxs to SmeMQQmwQW mmm£0>< :0 “0.:qu use .Fm>m4 .xmm we mpuaeem eoe emae .me.¢ a_nee uofluumflo mnvo. wave. mmvo. memo. ammo. mmmo. wave. Hmoo. omvo. Nmmo. Hmvo. ocwmuso uofluumflo mama. avmo. vmmo. ammo. ammo. sumo. vavo. mvmo. memo. Hume. «mmo. came. owflmcH ~5m¢. wove. whmo. vmmo. ammo. Hmvo. mmmo. onmo. move. move. ammo. some. quzmm uofluumwo nu .mmmo. wNNo. mama. enac. ammo. ammo. mvmo. mmao. ommo. mmao. mmmo. mwao. wofimuzo .nlc uofiflmg wwwc. vmmb. ammo. vmmc. cavc. mums. ovmo. name. mmmo. Homo. mmmo. mums. oUMmCH «MNQ. NMNQ. mama. ammo. vnmo. memo. vvmo. memo. mmmo. memo. vmmo. vvmo. @442 :oflumHsaom wNMQ. m§dd~. mvmo. mmmo. mmmo. vmmo. vomo. aamo. memo. Nmmo. came. Nome. mfigucm you SQQ £09m. QQQE SQQ .bum. 2mm: .me .95 com: $.50 .95 com: Son .cum cam: Sea .95 new: NWIQNQN. mmlmkmfi mhlnmmu shtmmma ohlmnma mnivpma muesmhxwmk us ufikuvfia x3 ham xmm \3 :38 :mxogm @3202 so .553:me “B 33:85; .ané «:2: ovmo. 5mm: mummo. cam: ooom. Hmooe oooo. Haooe oommo. Hmuomom mommo. Holomom moamo. oolmooo memo. moimood ooooo. moaooofi oooo. moaooofl odomo. oouoooa omomo. ooloeod oommo. oouoood ommo. ooioood oommo. oouooo2 Homo. oonoooa uoduumfio ovomuso uoquumoo mcamch oommo. :moz omamo. coo: moooo. :oaz odomo. eomz mommo. cam: oommo. somz 1n Hooo. fleece mmoo. Hobos ono. Amoco mooo. deuce mooo. deuce oooo. Hmooe 2 III" I'll III-all Ill-I'll I'll ll! 1: omoo. .2 mooo. .2 omoo. .2 «fivo. .2 omoo. .2 amoo. .m «moo. .2 oomo. .2 ommo. .2 . omao. .2 momo. .2 mmao. .2 HUMHHMHQ @Uflmgn—O UUHHHWMQ QUMmHSO HOflHumMD GUHmUSO HUMHHWHG QUflmuDO UOflhumflQ mfiwmuflo UUMHUWHQ @UHWUSO oommo. eaaz memo. cam: oomo. cmmz ommmo. coo: ommo. cooz Homo. :maz memo. deuce «moo. Haooe mono. deuce oooo. Hobos mooo. Hoooe mmmo. deuce Homo. .2 ommo. .2 memo. .2 memo. .2 Homo. .2 oomo. .2 oomo. .2 vmmo. .2 mono. .2 odmo. .2 Homo. .2 memo. .2 uoooumoo moomeo pomuomoo wofimcm Humoummo commeH oofluomoo moomco ooowomoo woflmcH unmoummo moomcH Holomoa oosmooa moloooa oolooom oelmoofi moloooq |lt 122 owwo. ommo. momo. oomo. com: oomm. Nome. oomp. mmwp. Pooch mmmo. quowoF pomo. _mnomQF ommo. _wnowmp ommo. pwuome mmvo. mwuwmm— ommo. omlmmmp omyo. mmawmmF ommo. onswnoP ammo. wknnnm— mmmo. wmimmoF owmo. wmummm— mnmo. wmummmp oroo. mmnonmr memo. muioomp owFO. mouQNmF mamo. nmuoum~ owwo. omlmmmp _nmo. onsmNmF mm—o. omummmF Pomo. omummop —w¢o. mononmp oFmo. mnuwnop Ffiwo. mononm— Nome. mnuvom— ouoeomoo oo_mooo ooooomoo moomoo mmFoEmo Loo Emommpcmmn< yo moopcmoemo Pooch com: ooooomoo woomooo oooeomoo ooomeo worm: Low Emowmpcwmn< we mompcwugmo FopOH com: mxoocoz Low powepmwo on oco xwm on Emwowpcmmo< mo moopcmoomo Fouoe com: .mm.¢ wPQoH |lt 123 3. Conversely, female staff members who live inside of the Davison district miss less time for absenteeism on Mondays (3.5 percent) than do female staff members who reside out- side of the district (4.84 percent). 4. Female staff members (4.17 percent) miss significantly more time for absence on Mondays than do male staff members (2.57 percent). Table 4.83 illustrates that there was a significant interaction en sex by district and absence time taken on Tuesdays. The rcher compiled additional statistical data on staff absence by sex istrict of residence for Tuesdays. This information is illuatrated bles 4.84, 4.85, and 4.86. The following conclusions are drawn this data: l. Staff members who live outside of the Davison School District are absent a greater percentage of the time on Tuesdays (3.59 percent) than are staff members who reside in the district (2.77 percent). 2. Male staff members who live inside of the district are absent slightly more often on Tuesdays (2.66 percent) than male staff members who live outside of the district (2.62 percent). 3. Female staff members who reside outside of the district are absent a significantly greater amount of time (4.56 percent) on Tuesdays than are female staff members who reside within the district (2.86 percent). ommmo. oomoo. oomoo. m mmo2o. oooeomoo 2o _o>oo 2o xmm ooooo. Noo_o. mmooo. m oompo. oooeom_o 2o 2o>oo wmmmmm. oooo2.o moeoo. 2 monoo. oooeomoo 2o xom oooom. Nmmo2. ooPoo. m momoo. 2o>oo 2o xom mm omomo. _ommm.o ommoo. _ ommoo. oooeomoo .1 oomoo. moooo.2 “m2oo. _ mm_oo. Amo 2o>oo mommm. Nomoo. momro. _ moNPo. 22o _o>oo mmomo. o_oom.e mpmoo. _ m_moo. xom o mo o meooom .o .o mmgmmom :oouow2o> mucoowowco_m :mmz oo Eom oo mogoom mmoomwoh :o Emommpcmmo< momgm>< co powgpmwo oco .pw>mo .xwm oo mpumwwm Loo pomp .mw.o opomk '1‘ 125 uofluumfia oomo. mmmo. mono. hmvo. ammo. oovo. ommo. omvo. oomo. Hmvo. oomo. homo. mvflmgso uofiuumfia ammo. momo. mono. oomo. ommo. mono. oomo. mmmo. memo. ammo. mmmo. momo. ocwm2H movo. Homo. momo. Homo. hmmo. memo. vomo. Nomo. mono. oamo. Homo. meo. m442um . uofiuumwa oomo. vomo. vomo. oomo. mono. mmmo. ammo. vomo. momo. mono. momo. ammo. mvfimuso uofluumoo ammo. ooao. mono. Nomo. ono. momo. oomo. vmmo. vomo. ammo. Homo. «moo. mCHmCH ommo. oHNo. ommo. vomo. Nomo. oomo. oomo. ommo. oomo. oomo. oomo. homo. agaz coflumasmom ammo. momo. mmmo. vmmo. ommo. ammo. momo. oomo. vomo. momo. Namo. oomo. ououcm pom .>0c .cum coo: .>wo .Uum 2mm: .>®D .Uum cam: .>oc .fium coo: .>wo .cum cow: .>oa .wum com: aoloooa mhnoooa ooioooa holoooa cosmooa moivooa WUCQDPWOZ .PO HUrLHW-D ~63 DEG K30 a: 2333 :DKDgfllnE 126 oomo. 222: 22mo. c222 oo2m. 22202 moo2. 22202 oooo. 2miomo2 mmmo. 2mlomo2 momo. o2lmoo2 ommo. o2um2o2 oomo. m2l22o2 oomo. m2n22o2 mono. 22io2o2 ommo. 221o2o2 2mmo. o2io2o2 2omo. o2sm2o2 oomo. 22-2222 oomo. o2no2o2 poauumfio mwflmuso uofluuwMQ wcfimcH mooo. 2202 mono. e222 momo. c222 Nomo. c202 2omo. e222 momo. c222 oomo. 22202 mmoo. 22202 om2o. 22202 mm2o. 22202 o22o. 22202 oooo. 22202 oomo. .2 2m2o. .2 oooo. .2 oooo. .2 mwmmg .2 22mo. .2 v2mo. .2 mmmo. .2 momo. .2 oomo. .2 momo. .2 mmmo. .2 wowuumwo mowmudo u02uumwo wwwmuso 20222220 wvfimuso avauumfla mvflmuso uofluumwo mcflmuzo uofluuwflo 002m290 mono. e222 ommo. e222 oomo. 222: ommo. 222: 2omo. 222: oomo. 2222 oooo. 22202 omoo. 22202 2ooo. 22202 222o. 22202 mmmo. 22202 22oo. 22202 momo. .2 mono. .2 oomo. .2 mmmo. .2 2omo. .2 momo. .2 oo2o. .2 mmmo. .2 momo. .2 .2mmo. .2 mmmo. .2 «moo. .2 vowuamflo mw2mcH unwuumwo 0U2w22 uuwuuwfla mewmcH yowuumwo mwflmcH unfiuumao mfiomcH avauumoo wvflmcH 2muomo2 o2zm2o2 m2u2oo2 22lo2o2 oouo2o2 22-2222 11' ||| 127 omoo. oomo. momo. oomo. 222: mmxm. m222. 22m2. nom2. 22202 mmmo. 2ouooo2 mmmo. 2oiooo2 ommo. 2mnooo2 mmmo. 2ouooo2 mmoo. omuw2o2 oomo. omiw2o2 wmmo. mulo2o2 2mmo. mmsmuo2 omvo. onummmP momo. @212202 mmmo. omu22o2 momo. wmumno2 omoo. 22lo2o2 mmmo. mmuomo2 oomo. nmuomo2 ommo. 22lo2m2 2moo. omummoF 2mmo. onummo2 momo. omlmmoF Nwmo. o2-mmo2 Ammo. mmiomo2 , momo. mmuomo2 ammo. mmuomm2 ommo. mnuouo2 20222m2o mowmuoo 2022pmwo mommCH 20222m2o mowmpoo 2022pm2o momeH mm22222 202 Emwmwpcmmo< mm—oz 202 Emwwmpcmmo< 20 mo22220202 22202 2202 20 wompcmu2mo 22202 2202 mxoom222 202 20222m2o 20 2:2 xmm >2 Emwmmpcmmn< 20 0o222202mo 22202 2222 .oo.¢ 22222 128 4. Female staff members are absent more on Tuesdays (3.71 percent) than are male staff members (2.64 percent). Table 4.87 indicates that there was no significant interaction en sex, level, or district of residence and staff absence on sdays. The Significance of F exceeded 0 (alpha) = .05 for every ble tested. Table 4.88 shows that there was a significant interaction between y district and absence time taken on Thursdays. The researcher red additional statistical information on staff absence by sex strict of residence for Thursdays. This data is presented in s 4.89, 4.90, and 4.9l. The following conclusions are drawn from data: 1. Staff members who reside inside of the Davison School District are absent more often on Thursdays (2.9 percent) than are staff members who live outside of the district (2.38 percent). 2. Male staff members who live inside of the district miss sig- nificantly more time (3.25 percent) on Thursdays than do male staff members who reside outside of the district (1.84 percent). 3. Female staff members who live outside of the school district miss slightly more time (2.91 percent) on Thursdays than do female staff members (2.55 percent) who live inside of the district. 4. Female Staff members are absent 2.73 percent of the time on Thursdays, while male staff members are absent 2.55 percent of the time. 129 omm2m. ooooN. mNNoo. N mmooo. 20222m2o on 20>02 20 xmm Nomoo. w2222. Pwmoo. N No22o. 20222m2o 20 20>02 .mwmmmn mo2oo.o mmomo. 2 omomo. 2022222o 20 xmm ooomN. N222m.2 2o22o. N omoNo. 20>02 20 xmm mo2m2. mNooo.N oomNo. 2 oomNo. 20222m2o 2mm2o. 2om2m.m oo2mo. 2 oo2mo. 222 22222 oo2mo. om2mm. o2moo. 2 o2moo. 222 22>22 2Nmmo. Noooo. 2mooo. 2 2mooo. xmm 2 20 2 02ooom .2 .o m022=0m 20222222> 00220222co2m 2202 20 Eom 20 002:0m ozoom2222 :0 Em2mmpcwma< 0o220>< :0 20222m2o oco .22>22 .xom 22 2200222 202 2222 .mm.2 22222 omooo. o2o22. ooooo. N ooooo. 20222m2o An 20>m2 >2 xmm oNoom. mmoNo. onooo. N omm2o. 20222m2o 2o 20>02 wNmNm. m2omo. o2o2o. 2 omo2o. 2022222o >0 xmm mommm. woN22.2 22N2o. N mmoNo. 20>02 22 xmm Noomm. mo2mm. oomoo. 2 voooo. 2022222o em2oo. mo2o2. o2moo. 2 o2moo. 222 22>22 222o2. mm2mo. ooooo. 2 ooooo. 222 22222 N2m20. mmooo. 2oooo. 2 2oooo. xmm 2 20 2 02ooom .2 .o m02200m 20222222> 00220222222m 2202 20 Eom PD 302330 vmwo. II I’lll'IluI-‘fli'llil I uo2ugm2Q 2vmo. momc. 2mmo. ammo. 2mmc. memo. mmmo. mmmo. mmmo. move. mm2wusc 20222mflo 2220. 222o. OHmo. 2mmo. memo. mmmo. memo. 222o. ammo. «22¢. qwmo. mmmo. vw2mz2 m2mo. mmmo. vmmo. 2mmo. 2mmo. 2mmo. ammo. mmHQ. 2mmo. vao. 2omo. mama. mqoe .oam :mmz .>wo .cgm cam: 4Mwa .cum cam: .>um;4mmw mmmm .>ma .cum cmoz .>oo .cum cams Mmlowmm m2-m2m2 MN-22NM NmnMMNm 2mm:m2m2 m2uwmmm wocmu2mmm 2o 20222m2o an ucw xwm An 2309 :meLm mzmvmgzc2 co Em2mmpcwmn< 2o mmmpcmu2w2 .mm.¢ w2pm2 ammo. cum: ammo. :moz thH. kuOB tha. HmuOE ammo. Hmlommfi wNmo. Hmlomma ommo. mhlmhma ommo. ahlmwmfi hmmo. mhlhhma VHmo. whlhhma mmao. hhlohaa mmmo. hhlwhma memo. whlmhma mane. whlmhma omwo. mhlvhma tho. mhlvnma uoauumfio wufimuso 9.27.3qu 3229; 1| mNNo. cam: ammo. two: th0. :mw: mwao. cam: moms. :mwz omNo. cmw: MN mmvo. ACHOB mmvo. HmuOB vmmo. HMUOE hhmo. kuOP wove. aMHOB ammo. HMUOB vaOM .m vomo. .m ammo. .h Nome. .m NmNo. .h move. .m Howe. .2 mmdo. .2 wwwo. .: tho. .2 vao. .2 «mac. .2 uofiuamflc mgmuso vowuumdo wvwmuno uofiuumwo wgmaso uofiuumfio ovwmuzo uofluumfin mvfimuso avauumao mvflmuso ammo. cam: omNo. cam: «HMO. Cmmz mmmo. :mwi mane. :60: tho. :mwz wmwo. Have? ammo. AmuOP wNwo. HMHOE envo. HmuOB wmwo. HmuOE mmmo. AmuOB Mhno. .h eNNo. .h NNNO. .h vhao. .m vane. .m mNNo. .m mmNC. .2 mmmo. .2 move. .2 meo. .2 NNmo. .2 meme. .2 pawuumfln wmimcH gamuumwo 023.922 ”2022539 wgmcH uofiuumfio ocflwCH uoauumflo 0222922 goduamao mcwmzH 3.222312 2.223 22.223 22.2222 221.223 2-3.3 8.2.3.5 .3 28 E 132 2mNo. mmNo. vm2o. mNmo. :00: ovm2. Nmm2. mo22. omm2. 20202 ¢mNo. 2muomm2 mnmo. 2wnomm2 2oNo. 2muowm2 moNo. 2wnowm2 momo. mmuw2o2 vNNo. mnlw2m2 mm2o. m2-m2m2 mmmo. o21w2o2 wNmo. w2122m2 NNNo. w2I22o2 memo. m2|22m2 oo¢o. wmnnmm2 NoNo. 22lo2m2 #22o. mnuo2m2 m22o. 22:02m2 omNo. 22:02m2 NmNo. onum2m2 v2mo. omummm2 ¢m2o. o21m2m2 NNmo. ©21m2m2 mo¢o. m2u¢2m2 mNNo. mms¢2m2 «m2o. m2n¢2o2 womo. m2102m2 20222020 0022200 20222020 002002 0020502 202 50200pc0mn< 20 0002000202 20202 :00: 20222020 0020200 202me2o 002mc2 00202 202 Em200pc0mn< 2o 0002:00202 20202 :00: 020002052 202 20222029 20 0:0 x0m an 50200pc0mn< 20 0002000202 20202 :00: .2m.q 02302 \IIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIhHHHillI-I TabTe 4.92 iiiustrates that there was no significant interaction tween sex, Tevei, or district of residence and staff absence on idays. The Significance of F exceeded a (aipha) = .05 for every riabie tested. st for ReTationship Between Age and erage Absenteeism bx Days of the e5 Regression anaiysis was used to test for the reTationship between e and average absenteeism by day of the week. The significance Teve] which these tests were conducted was set at a (aipha) = _05. TabTes 4.93 through 4.97 indicate that there were no significant Tationships between age and average absenteeism for any day of the ek. sts for Effects of Sex, LeveT, and strict on Avera e Absenteeism by ths of the Year TabTe 4.98 iiiustrates that there was a significant interaction tween Tevei and district and average absenteeism in September. The searcher gathered additionai statisticaT information on staff absence level and district for September. This data is presented in Table J9 and Table 4.100. The foiiowing conciusions are drawn from this a: T. The percentage of absenteeism for September was reiativeiy very smaTT (1.4 percent). 2. Staff members who Tived inside of the Davison SchooT District were absent siightiy Tess often (1.31 percent) than those staff members who resided outside of the district (1.41 percent) 20000. 2.2000. N800. N 00200. 0.0.2.5920 .3 200,3 3 am 02000. 20020. 00.200. N 0020. 0.0.2.5020 23 20.23 0N0; 02020. 02.200. 2 02200. 0.0.2.5020 20 Sam M0022. 2022N.N 20000. N 02000. 2023 .3 x00 4 00200. N2 200. N0000. 2 N0000. n20 2:0 .20 B 00200. 20N20. 00200. 2 00200. ANV 200,00 02002. 022N022 0080. 2 00.80. E 20.20.. N0200. N0002. 00000. 2 00000. X00 2 2o 2 020:0m .2 .o m02000m 00220220> 00000222cm2m :00: 20 50m 20 002:0m m>00222 :0 50200pc0mn< 00020>< :0 20222020 0:0 .20>00 .x0m 20 m20022m 202 pm02 .Nm.¢ 02002 iIIlIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIMHHHI-IIII 135 /f wnmom. Nvmqm. oo2oo. mooNo. omooo. 0o< 2 20 0000 m 000200> 00000222002m oo 0m000> 00000000o .5002 00002 0220o 020023 002 020x200< 0020000002 0000000003 00 0020000000< 0m000>< 000 0m< 0003000 020000200202 000 002 0002 .mm.0 02002 .iuiiiiiiIiIii.iIiIIiiiIIiiiiiIiiiIiiIIiiliIiiIiiiiiiIiiiiiIiIiiIiiIliiliiiililiiliilii...iili mmmmc. mom20.u oo2oo. 22Nmo.u 2wooo.i 0m< 00202-2 00000 .000 2 20 0:20>-2 00002 .000 0000 m 000200> 000002220020 0m000><|-0200200> 000000000 .0002 00002 0220o 020022 002 020x200< 0020000002 00000002 00 0020000000< 0m000>< 000 0m< 0003000 020000200200 000 002 0002 .0m.0 02002 2022m. mvmoo.2- ww2oo. mooo2.u mw2oo.u 0o< 0:20>-2 00002 .000 000m m 000200> IOU 136 0m000. mmmmm.u 00200. 02200.- 00000.: 00< 2 00 0:20>-2 000000000000 20002 .000 0000 0 000020> IOU HHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH 00020><--0200000> 000000000 .0202 00202 02200 000003 200 0000200< 0000000000 0000000 00 0000000000< 00000>< 000 00< 0003000 000000000200 000 200 0002 .00.0 02002 l/I/ 00020. 20mm0.- 00200. mm2mo.u 20200.- 00< 2 00 0:20>-2 00222 .000 0000 0 000020> 000000000000 00 IwIwIIMrIIMIIIrIhIHLuLHhUHUHHHHHhHHHHHMwhwhwhHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH 00020><--0200000> 000000000 .0002 00222 02200 000003 000 0000200< 0000002000 MKMUWLJC_ CO EWPQwJZDAD: DmU_U>—k 3:5 JD: ..))..)’) L ....... 137 I..0II.IiIIn.I..1.I.IIII.1IIII1IIIIIIIIIIIIIIIII.I.I.I.I.IIIIu1IIIII.I.IIIl.l...1.l..ll|.|.|.....l 00000. 22N02. 00000. N 00000. 00000000 00 00>00 00 000 00000. N000_.0 0N0No. N 00N00. 00000000 00 00>00 000N0. 0N000. 00000. 0 00000. 00000000 00 x00 00000. 0000N.0 002No. N 00000. 00>00 00 000 00000. 00000. 0N000. _ 0N000. 00000000 00000. 0NN0N. 00N00. 0 00N00. 0N0 20>00 0000N. 0000N.0 00000. 0 00000. 200 00>00 00002. 00020. 00000. 0 00000. 000 n— ..20 n— 000: m .0 .0 00.20: m 00.50.20"; 0000000000000 0002 0.8 000 00 002000 000000000 0.0 00000000000. 00000>< 00 000000.00 000 .20>0._ nx00 000 00000002 0000 0002 .000 0302 JUdhumMD 0000. 0000. 0000. 0000. 0 0 0000. 0000. 0000. 0000. 0 0 0000000 uofluamao 0000. 0000. 0000. 0000. 0000. 0000. 0000. 0000. 0000. 0000. 0000. 0000. 0000:0 000:00 0000. 0000. 0000. 0000. 0000. 0000. 0000. 0000. 0000. 0000. 0000. 0000. :00: 000200 . Isl!IIIIIIIzIIIlllltnlrlllllllllnllrllIIIIIIIIIIIIIIIIIIrIt (IIIIIIIIIII .IIIIIIIIIIIIIIIIIII uoflpumflo 0000. 0000. 0000. 0000. 0000. 0000. 0000. 0000. 0000. 0000. 0 0 0000000 . 00000000 00 0 0 0000. 0000. 0000. 0000. 0000. 0000. 0000. 0000. 0000. 0000. 000wcH 3 1: 000:00 0000. 0000. 0000. 0000. 0000. 0000. 0000. 0000. 0000. 0000. 0000. 0000. :00: 000200 :IJIJIJIIIIIIIIIliitItI«IIIJIIIIIIIIIIJIIIJIJIII. . .IIIIIII1IItIIIIIIItIII1IIIIIIIJIIrIIIIIIIIIIIIIIIIIIIIIIIII uowuumwo 0000. 0000. 0000. 0000. 0 0 0 0 0000. 0000. 0 0 0000000 00000000 0000. 0000. 0000. 0000. 0000. 0000. 0000. 0000. 0000. 0000. 0000. 0000. 000mcH 0000. 0000. 0000. 0000. 0000. 0000. 0000. 0000. 0000. 0000. 0000. 0000. 0:40202000 II .rlzlllllllllxlrlrltixt: IIIIJISI II11IItII1III1sIIIiIIIII1IIIIIIIIIIIIIIIIIIIIIIIIIII :oflumHDQOQ 0000. 0000. 0000. 0000. 0000. 0000. 0000. 0000. 0000. 0000. 0000. 0000. 0:00:0 :00 .>00 nmwm :00: .>00 .000 M00: .>00 .000 :00: .>00 .0wm mMmm .>0: .000 :00: .>00 .000 :00: 0010000 mmn0000 00-0000 00-0000 wml000m 0010000 [IIIHTI I!!! 'l/lll 139 IIIIIIInIIIII:IxuInIIIgIxIluuIIIIIsIIIIIIIIIIIu.IpIIuIIlIIIIIIIIIuII|Ixnullnllllllxlzlnlnlnllul 0000. 0m—o. wocmmn< :00: :00> xwm mmmo. mNFO. pwuommF ommo. 0Nmo. mnnmmm— mmoo. 0moo. w0u00m0 Nmoo. mmoo. 00:00a— mmmo. m000. omummm— o 0:00. m0u00m0 If!!! 00000000 0000000 00000000 000000 000500 0m :00 00:000000 00 0000000: 0 00:00:: 0000m mmoo. wmro. _mNo. wmoo. mmoo. mmro. wocmma< :00: :00> x0m mFNo. mwFO. wwvo. o mmoo. ¢m00. 0wuowm0 omoo. Nmmo. mmdo. . memo. :mpo. meO. mnlwmmr o 0000. mmpo. wN—o. o mmoo. wmummmfi 0000. mooo. 0000. mwoo. o N000. mmummmp owmo. wwpo. Nmmo. w0oo. mm—o. wmmo. o0um0m0 o cows. 0 mmoo. o mmoo. mmuvmmr 00000000 00000000 00000000 00000000 00000000 00000000 0000000 000000 0000000 000000 0000000 000000 0000000 00000 0000000 00000 0000000 00000 000:0m :00: :00: 000:0m :00: 000::0 :00: :00pcmsmpm :00: .I....I.IIIIIIxI.I..IIpIItIIIIIIIII.I.II..l.I.I.I;IIIIIzIIIII.1IIlIIJ.1IuIIII.11..|||.l.|l..1[.|1.|.. 140 3. Elementary staff members who Tived inside of the Davison district were absent twice as often in September as eTementary staff members who resided outside of the district. 4. Junior high schooT staff members who Tived outside of the Davison district missed nearTy three times as much work in September as those staff members Tiving in the district. 5. High schooi staff members residing inside of the Davison Schoo] District were absent over han again as much in September as those staff members who Tived outside of the district. TabTe 4.101 indicates that there was no significant interaction veen sex, Tevei, or district of residence and staff absence during )ber. Tabie 4.102 shows that there was no significant interaction Teen sex, Tevei, or district of residence and staff absenteeism in mber. The Significance of F exceeded a (anha) = .05 for every abTe tested. TabTe 4.103 iiiustrates that there was no significant interaction een sex, TeveT, or district of residence and staff absence during nber. Tabie 4.104 indicates that there was a significant interaction zen sex by district and absence time taken during Januarys. The 1rcher further investigated staff absence by sex by district of lence for Januarys and has presented that data in TabTes 4.105, 3, and TabTe 4.107. The conciusions drawn from this data are: 141 NNmNm. mNNm—.~ quNo. N mwaqo. powxumwo An Fm>w4 An xmm waqm. _aqu. onoo. N Nmmoo. puwcpmwa An —m>m4 mmmmN. opmo_.r meNo. _ meNo. poecpmvo An xmm oom¢_. Noomm._ memo. N omwmo. _m>m4 An xwm w¢_oN. ownmo.r omNmo. _ omNmo. puwcpmwa 3%. 58. 2:8. F 2:8. Q E3 Noomm. oNFQO. moooo. _ moooo. AFV Fw>w4 mmmmm. mwNmm. oomoo. F ooooo. xwm L mo m wcmsvm .m .o mogmzcm coeuwwcm> wUCMUmecmwm cam: 40 Ezm mo muczom LwnEw>oz :w Emwmwpcmmn< wmmcm>< co powcpmwa Ucm ,_w>w4 ,xmm mo mpumwmm Low pmwe .No_.¢ mFame wmmmm. FQMNO.— cum—o. N mammo. wowcumvo An Fw>w4 kn xmm ommwo. momov. mmmoo. N mmmpo. puwgpmwa >5 ~w>m4 mNomo. NNNom.m wwvoo. — wwwmo. pquumwo zn xwm mfimmm. mmomm. FQFFO. N NONNo. Fw>w4 An xwm Noomm. mmmoo. woooo. — woooo. powmewo mpmmo. chwN.N Nmmmo. _ Nmmmo. ANV ~m>w4 mooop. mromm.N wmmmo. F vmmmo. A—V ~w>w4 mooop. mvoom.N Fmrmo. — Fmpmo. xmm a we a mcmzcm .u .o mmcmzvm coepmVLw> oucaowwvcmwm com: me Ezm we moczom 142 rome. Pmdmr. mmeoo. N wmmoo. Heatwave Na _osas An xmm FommN. Pmeom. NmNoo. N amm_o. powcpmwo an _m>ms .mmmmmq «NFNm.¢ mmm_r. _ Nmm_F. pawcmeQ an xam Noomo. ONNNN. ommoo. N NFmPo. Fa>ws an xmm ooeNm. m_moo. mNooo. _ MNooo. pawcbmwo “moss. MNmeP.N epmmo. P e_mmo. ANV _a>as eNmNN. Nwm_o. _mooo. _ _mooo. A_v _m>ms omme. mNeNo.N mm_mo. P mmFmo. xmm u mo m mcmzcm .u .o mmcmzcm cowumwcm> mocwowmwcmrm :mmz mo 53m mo muczom xcmscmw :w Emwmmycmma< wmmcw>< :o puvcpmeo vcm h_m>m._ ,xmm mo mpuwmym com pmme .wo—.¢ mrnmp mNmme. Nemmo. ommNo. N omomo. bawcpmwo an Fm>ms an xam Noomm. N_~NP. mmeoo. N onoo. powcpmwo Na Pm>ms NNeNm. memwm. Nmmmo. N Nmmmo. puwcpm_a Na xmm ONmom. ¢N__o._ mmmmo. N m_mNo. _msms Na xam moemo. NmmNN. mNmoo. _ onoo. paeapmmo NONMN. msmee._ NeNmo. F NeNmo. ANV Fa>as ONONQ. emON_. N_©oo. _ N_©oo. AFV _a>as Nmm_m. NNONe. ONm_o. F ONmfio. xmm u do a mgmzcm .L .Q mmcmzcm cowpwwcm> mocmowmwcmwm :mmz 40 Sam mo muczom 143 uofluumfio qmvo. ammo. mmNo. mmmo. Nmao. Home. Nflco. ammo. ammo. ommo. ooec. nflwo. wcflmuso uufluumfio mmcc. ence. mace. moNo. mmmo. News. onNo. veNo. oomo. memo. cmvo. mNmo. moemcH heme. eveo. oceo. mmNo. eNmo. NNQO. oveo. maNo. Nvmo. mmao. ammo. NNqo. maoo .cum :moz .>oa .wum wee: .>ao .cum :maz «wwm-.amw mam: .>oo .wum coo: .>oo .wum :moz mmummaq NMumem mmnMemN MMHWMNM enumemfi meiveafi mucmuwmmm mo puwcwmwm use xmm an czoa :mxocm mxcmzcmw cw Emwmmpcmmn< do mmmpcmucma .mo_.¢ wpnme 144 vane. hmwo. ammo. Home. uofluumwo meme. mama. vuvo. vmmo. cam: HmuOB .m .2 weemuso cam: Hayes .h .2 uofluumflo ocwmcH dmaomma vomo. mcvc. mmmo. .h mwdo. .E uofiuumfio mcmo. have. memo. .m Nch. .2 Hmmo. hmma. vamo. vomo. ammo. mmmo. Heme. vmvo. :moz Hmuoe Hmlomaa mhlwhmm mhlhhmd whiwfima whlmhmd meleema uoauumae uowuumfio wwmeH mhlmhma cam: ku09 meflmuze :mw: Neuoe meemueo Hams. :wo: ammo. Hmuos meme. .m owmc. .2 . uONHumwo mcfimuzo mvvo. cam: name. Hmuoa weve. .m wmvc. .2 uowuumfia wcwmcH mmlhhmd uofiuuwwo ammo. vxmo. veao. oavo. Nvmo. cam: mmom. kuoe meme. Neneema meme. eeieeea eeee. enuneefi NeNe. enieeea meme. eeimeed move. meleeea uofiupmfio mcflmcH Naboe Neee. .e emme. .2 Nmae. wwfiwuso uofluumfio :60: ¢qm00 Nmuoe neee. .e mwmmd .: «Mme. uofluumwo wflmeH hhlwhaa 5mm: Nmeoe .m .z meflmuso :mmz deuce .e .2 HUHHumfiQ wfimeH MMH mhma vmvo. some. I!" name. omNo. uowuumfio move. came. mmmo. mmvo. cam: Heuoe .m .z wefimuse :mmz Nmuoe .m .z uowuumflo mnflmcH mhlvhma 145 omqo. vwmo. NFNo. owmo. :emz CONN. NmON. omNF. Fvom. FeHOH ammo. _wlommF envo. _wuome FqNo. _miowm_ #NNO. _wiome mMNo. mmuwmmp mmNo. mulwmmF mm—o. mmuwan NmFO. mNINNQF meo. mmnmmmF _mwo. wmimmmp ooNo. wmummm— mmwo. wmummm— meo. Nnuomor «NFC. mmuwmmr vFNo. mmlomm— o—¢o. mmummmr ommo. omummmr memo. mmnmmmP NMFO. mmummmr wmmo. mmumnmr n—mo. mmuwmmy mNmo. mmu¢mmF omNo. mmuwmmfi mm¢o. mmudmmp eorcpm_e meemese eewcem_e meemcH mepesme Lee Emwewpceme< me emepceecee Pepee :eez eewcemwe weemese paecemwo mewmee meFez Lew Emeeepeeme< we mmepceocee _epok :emz Aceecme Le+ uuvcpmwo me use xmm ze Emeeepceme< ye emepceecee Fewee :eez .mo_.¢ wreak ||I_ 146 1. Staff members who reside inside of the Davison Schoo1 District miss s1ight1y more time for absence (3.42 percent) during Januarys than do staff members who 1ive outside (3.31 percent) of the district. 2. Ma1e staff members who 1ive inside the district missed more time (3.40 percent) during Januarys than did ma1e staff members (2.12 percent) residing outside of the district. 3. Fema1e staff members who reside outside of the Davison district were absent 4.5 percent of the time during Januarys, whi1e fema1e staff members 1iving inside of the district were absent 3.44 percent of the time. 4. Fema1e staff members were absent a greater percentage of the time (3.97 percent) during Januarys than were ma1e staff members (2.76 percent). Tab1e 4.108 shows that there was a significant interaction n sex by district and absence time taken during Februarys. The her further reviewed staff absence by sex by district of residence ruarys and presented that information in Tab1e 4.109, 4.110, 11. The fo11owing conc1usions were drawn from this information: . Staff members who 1ive outside of the Davison district are absent more often (3.79 percent) during February than are staff members who reside in the district (3.7 percent). . Ma1e staff members who resided outside of the district were absent more often during Februarys (3.95 percent) than were ma1e staff members who 1ived within the district (3.42 percent). 147 if; oovmm. meowo. MNFoo. N meNoo. pchmeo an Fe>e4 An xwm memem. meeem. FemFe. N Feeme. powcemFe Ag Fa>me wflmmma. memee.e FemNF. F FeeNF. mmflummflmlxmimwm eeNem. NNNFe. eeeee. N Feeee. Fa>as en xam eFme. omNNo. mmooo. F emooo. Fchmee mmoFo. qumN. Romeo. F moooo. FNV Fw>w4 monN. meoF.F mwomo. F mwomo. FFV Fw>m4 mwao. wommm.m FmFmF. F FmFmF. xwm m Fe m eceeem .e .e mecemem :erche> meceeFFchFm see: we Ezm Fe weceem xceeceem cF EmFeepceme< emece>< :e pchmee use .Fe>e4 .xmm Fe mpeeFFm LeF pmeF .moF.e eFeeF 148 II If in, 11111111111. 11111111111111111111 , . . . me. heme. mmve. evae. . . . . emme eeee emme me . meme meme emee mNme. neve. oMmewwm mmee. emme. eFee. emve. meme. meme. move. mvNe. meme. meme. meme. eeve. yumuumme . . . . . . mm: mCH . . me eeme Feve meme mmee. . . . eve meme Fmee eeme «N Nmme e . . e 1111. pee vae eqoe .eem meow 4wmm14wmm mMmm -wNMe1nwmm mmwm awmm14mww Mmmm .>oe .cum cam: mmmmmwm mmumwmm MMHMMNM mmnwmmw mmnmmmm meswmmw meceeFmem Fe pchmeo use xem me :zeo :mxecm xgeeceem cF EmFmepcwme< Fe wmepcwegwe .moF.¢ anwH 149 thc. :mOZ mmee. maeoe vevo. .m ammo. .z uommemme mmmmueo memo. thN. hmmc. ammo. hvmo. mvvo. hmeo. ammo. cam: HmuCB Hm1omma mhlmhaa mhlhhmu phlonmd wh1mhmH mn1vhmfi memuemme 'llllll uomuummo mammuso mamwuso memo. mooo. mmeea eeme. :moz HmuOE .h .2 uowuummo mcmmumm Ohmo. cam: mme. Fmeoe wave. me1emmm emme. mm1emmm mmme. emnmmmm meme. mmnemmm meme. emummmm emme. mm1emmm ammuemme memmcm meme. new: mmme. new: emme. meeoe vmme. memos mmmma .e mmme. .m meme. .2 mmme. .2 uomuummo OUmmuso [I‘ll uomuumma wvwwuzo mmve. see: emme. sew: mmee. sew: meme. sea: mmee. cam: emee. meme? mmee. meeoe mmme. Feeee mmme. Fmece meme. mmuoe mwmmq .m mmee. .m ane. .e evme. .e meme. .e meve. .2 meme. .: meme. .2 meme. .: mFme. .: wmwuuwmc onmmcm uommewme oommqm wmmHummc ocmmcm AMMmumwmlmmwmmm bummmmmo mowmcm mmnmmmm anmmwm emummmm MMHWNNM em1mmmm 9). Tani.) 1’...) I32) 5). 35.55-31 ammo. cmwz mmwo. quOP nnvc. .m Node. .2 wwmuumwo QWkuso @mmo. cmoz tho. Hence move. .b memo. .2 [1"]! momuuwmo ovmmcH 150 mNmo. mmmo. mmmo. Nemo. :emz mmFm. Femm. eemN. NmeN. Feeow mmee. Fm-emmF emme. Fm-emmF mFme. Fe1emmF Neee. Fm-eemF meme. mm-emmF emee. mm-emm_ emme. mm-emmF FeNe. mm1eNmF mFee. em-NNmF meme. em1mmmF m_me. em-mmmF Feme. mm-mmmF meme. mm-emm_ meme. mm-emmF mmee. mm-emmF mmNe. Nm1emmF mFNe. em-mmmF meme. em1mmm_ mmee. em-mmmF mFme. em1mmmF mmme. mm-emmF eeee. mm1emm_ eNme. mN1eNmF NmNe. mm-mmmF emweemwm mewmeme Homemmwe mewmem pewtemem mewmeme 11 meFeEem Lew EmFeepceme< we mmepceegee Fepew gee: powgmeo wewmcF meFez cow EmFeepeeme< 111. we emepcmegee Fepew ceez mgeegeee Lew pchmeo me use xem he EmFmepceme< we emepceeeee FepeF :eez .FFF.¢ aneF 151 3. Fema1es who 1ived outside of the district missed significant1y more time during Februarys (5.29 percent) than did fema1e staff members who resided within the district (3.97 percent). 4. Fema1e staff members were absent 4.63 percent of the time during Februarys, whi1e ma1e staff members were absent 3.69 percent of the time. Tab1e 4.112 indicates that there was a significant difference in teeism taken in March by 1eve1. The researcher gathered additiona1 stica1 information on staff absence during March by 1eve1. That is presented in Tab1es 4.113 and 4.114. The fo11owing conc1usions irawn from that data: 1. E1ementary teachers were absent for the greatest amount of time during March in three of the six years studied, the second greatest amount of time during two of the years, and missed the 1east amount of time during one year. Junior high schoo1 staff members were absent for the greatest N amount of time during March in three of the six years studied, the second greatest amount of time during two of the years, and missed the 1east amount of time during one year. . High schoo1 staff members were absent for the second greatest amount of time in March during two of the years studied and missed the 1east amount of time during the other four years. . E1ementary teachers were absent for the greatest period of time in March during the six years studied, junior high schoo1 teachers were absent the second greatest amount of time, and 152 owemm. wNmeo. emcee. N meFoo. Fewwpmwo me Fe>e4 me xem emcee. eommm.N memeo. N mNmmo. powgpmwo we Fw>e4 eemoN. NNvFe.F ommNo. F ommNo. puwgpmwo an xem mNmmF. emmee.F emmNo. N mwmmo. Fe>e4 me xem mmem. mFmNo. oeFoo. F oeFoo. puwgpmwo FFmoo. NoFmF.m FemNF. F FemNF. FNV Fe>e4 meNN. NmmFN.F FFNNo. F FFNNo. FFV Fw>we mmmFm. wmemo. ooFoo. F ooFoo. xem ._ 2mm . . mew meme some: :F EmFeepceme< emege>< :e pewcpmwo ece .Fe>e4 .xem we mpeewwm Lew pmww 1] (I, .NFF.v eFeew 153 J; mmme. mmme. emme. eeme. emme. mmme. meme. mmme. mmme. mmme. Foozom mmme. meme. :mm: momemm . . . . . OO~ O emme. mmme. vmwe. emme meme emme meme mmme emme. mmme. mmme. meme. new: womhsw meme. emme. mmme. meme. mee. mmme. meme. mmme. mmme. meme. mee. mee. mmmucoEaFm . . o . . . COH M emme. mmme. eeve mmme emee meme mmme mmme emme. emme. evme. emme. muwwcwewwm 4wmm1qmmw sea: .>me .eum sea: .>me .eum new: dwee deem seam wwmm1.eem cam: .>we .eum ewe: mm1emmm NM1mmmm mm1mmmm mm1emmm mmummmm mm1mmmF Fm>wm me ecm mmmm> me czeo :exemm some: cw Emwmepceme< we emepcmemwe .mFF.¢ mFeeF 154 moNo. meo. mmmo. :mmz ommF. mNNN. NmmN. Fmpew wFNo. mmFo. emmo. Fm1ommF eONo. emmo. memo. mm1wmmF mFNo. ommo. Nmeo. wm1mmmF mmNo. Femo. ammo. mm1emmF mmNo. mFeo. Foeo. em1mNmF memo. memo. meo. mm1emmF epem eecmme< :mmz epmm euceme< cmmz mpmm eecmme< :mmz LemF Feecem new: mchem Feecem mow: mewcee mmmpcmEmFm Fm>wm he czoo :mxegm :mcz some: Low wocmme< wo mcemz we mewgmsssm .vFF.e mFemw 155 high schoo1 staff members missed the 1east amount of time during March for the six years studied. Tab1e 4.115 shows that there was no significant interaction between 1eve1, or district of residence and staff absenteeism during Apri1. Significance of F exceeded a (a1pha) = .05 for every variab1e tested. Tab1e 4.116 i11ustrates that there was a significant interaction aen 1eve1 and district and average absenteeism during May. The archer gathered additiona1 statistica1 information on staff absence eve1 and district for May. This data is presented in Tab1es 4.117 1.118. The fo11owing conc1usions are derived from this data: 1. Staff members who 1ived inside of the Davison district were absent 1ess often (2.7 percent) in May than were those staff members who resided outside of the district (3.8 percent). 2. E1ementary staff members who resided in the district were absent 2.6 percent of the time in May, and e1ementary staff members who 1ived outside of the district were absent 3.5 percent of the time. . Members of the junior high schoo1 staff who 1ived outside of (A) the district were absent in excess of twice as often (6 per— cent vs. 2.7 percent) as were staff members 1iving inside of the district. . High schoo1 staff personne1 1iving outside of the Davison mp district were absent on1y s1ight1y more (2.9 percent vs. 2.8 percent) than staff members who 1ived inside of the district. 156 vmmmo. Nwooo. N meFee. mememFm mm Fm>mm mm xmm meFe. emmme.m Fmeem. N mmFNF. weFmemFm me Fmsmm FemFe. mmemm.m mFeme. F mFeee. eeFmemFe me xmm eemmm. FmNmF. FmNee. N Nemee. Fm>mm me xmm eeeee. mFeee.m mmFee. F mmFee. eememFm mmFmN. FNmFe.F mFNNe. F mFNNe. FNV Fm>mm mNeem. memme.F FmeFe. F FmeFe. FFV Fm>mm mmeFm. FmFme. mFeee. F mFeme. xmm 1._ 05 m 9.8: m .u_ .o mem: m 20.5072; mesmewwwcmwm :me: we Eem we eemzem me: :F Emmeuceme< ememm>< :e peFmeFm ece .Fm>mm .xmm we mmemwwm mow mmmF .eFF.m mFemF meNNm. ememe. mmFee. N mmNee. eeFmemFm Fe Fm>mm me xmm emmmm. eeFee. meeee. N moeee. mememFm mm Fm>me NemFF. memF. mmNee. F meNoe. methmFm me xmm Fmemm. mmFFF. emNee. N eeeee. Fm>mm mm xmm memFm. eemNe. emcee. F eeeee. eethmFm mmmFe. NmNmF.m ememe. F ememe. FNV Fm>mm mmmeF. eeFFe.N mFeee. F mmeee. FFV Fm>mm emmmm. eemme. mmFee. F mmFee. xmm L we e meme: m cermme> moceuwwwcmwm new: we Eem _3 ua_:>7 f/ uomuumwa mmme. mFme. mmme. mee. mmme. meme. mmme. emme. meme. mmFe. mmee. emme. memmeso mommmmma mmme. mee. mmee. mmme. meme. mee. mFNe. mmFe. mee. mmme. emme. meme. weNmCH eeo=em meme. mmNe. mmme. mmme. mmme. meme. mmme. eNNe. meme. mee. eeme. eeee. :uF= memzmm 1111111111111 111111111111111111111111111111111111111111111111 111 11111111 111111111 uUAuuch mmme. emme. mmNe. meme. mmme. meme. mNme. mee. meme. eeee. meme. emme. oemmmzo momummme meme. meme. mmme. emme. eeee. emme. vae. mmme. meme. meme. emme. meme. oemmzm Joceum 7/ emee. meme. mee. emme. mmme. meme. emme. mee. eeve. emme. mee. mNme. :eH: momzee w 11111;.11/11 1 (1 unmuumFo mFme. emme. mmme. mmee. mee. mmme. mmee. mFme. emme. mmme. emee. mmNe. aemmuse momuumme emwe. mmme. emme. emNe. meme. vmme. mFee. emme. mee. mmme. emme. meme. oemmcm emme. meme. mmme. evme. mee. meme. mFee. mmme. FFme. emFe. mFme. mmme. mmmezmzmqm 1111111111111111111111111111111111. .111111111111111111111111111111111111111111111111111111111111111111111111 comumHJLCm mmee. mmme. meme. emme. emve. mmme. meme. emme. mmme. mmme. mmve. mmme. ammucm mom 4Noe .emm :mm: .>oe .eem seem .>me .eum new: ammo .emw cam: uwmm .eem cam: wwwe .eum sea: mm1emmm NMnmmmm mm1mmmm MMummmF mm1mmmm mm1mmmF LMW> >.Q JJ—LJO_3 53 3:5 .J-Jl. 5.: ..... I 158 mwmo. NmNo. eeceme< cmez mmmF me quo. FmNo. Fw1ome emNo. moNo. mm1mmmF ommo. NmNo. mm1man ammo. omNo. mm1mmmF mmFo. FmNo. wm1mmaF mmqo. mmNo. mF-eFmF mememFm memeze eememFm meFmeF FmNe. FFNe. eeee. NFNe. mmme. meNe. FFme. FFNe. emFe. meme. emme. mmNe. FNFe. mmNe. mmNe. eFNe. mmmm. emNe. mFNe. FmNe. meme. emme. mee. emNe. eFNe. mmFe. FFme. mmFe. FFme. eFme. mmFe. FFNe. meme. mFme. mNFe. mNNe. emme. Feee. mNme. meNe. mmNe. meNe. meFmemFm eeFmemFm eaFmemFm mamemFe mamemFm FaFmemFm meFmeze meFmeF meFmeze meFmeF memeze mechF 11111111111111111111 easemem wweem easemem wwmmw . meemmm< wwemm Feesem saw: :me: Feezem :mFI mewcee :mez AmmuceEmFm :eez 111111111111111111I111111111111111111111111111 meceme< cmmz Lme> xwm Fw1ome mm1wmmF wm1mmmF mm1ommF mm1mNmF mm1¢an A In” 159 Tab1e 4.119 shows that there was no significant interaction een sex, 1eve1, or district or residence and staff absence during ; for Re1ationship Between Age and 1ge Absenteeism by Months of the Regression ana1ysis was again used to test for any significant :ionship between age and average absenteeism by month of the year. ignificance 1eve1 at which these tests were conducted was set at pha) = .05. Tab1es 4.120 through 4.129 i11ustrate that there was no significant ionship between age and average absenteeism for months of the year. 4.128 shows that the Significance of T is .03322, which puts it the a .05 1eve1 and indicates that there was a significant re1a- iip between age and average absenteeism in May. However, the ‘cher discounts this particu1ar finding. Since the re1ationship 1n age and average absenteeism for every day of the week and every month of the year was not significant, the researcher fee1s that 1ationship between age and absenteeism in May just happen by and is not significant. for Effects of Sex, Leve1, and District “age Absenteeism by Reasons for 11ness 'ab1e 4.130 indicates that there was a significant re1ationship sex by district and staff absence for i11ness. The researcher ' s d additiona1 statistica1 information on staff absence for 111065 4___.- 160 I? eFmeN. NmmNe.F eeNNe. N Nemee. meFemmFe me Fe>ee me xem mmmme. emmFm. Neeee. N meNFe. eeFeemFm me Fe>ee NeFFF. mmmmm.N mmeee. F mmeee. meFeemFe me xem mFemm. mmmee. eeeee. N NFeee. Feeee me xem FeeeN. mmee.F NmmNe. F NmmNe. eeFemmFe NeemF. FmFFe. mFFee. F mFFee. FNV Fe>ee Neme. NFeFe. FNeee. F FNeee. FFV Fe>ee mFmFF. mmee. NmFee. F NmFee. xem L Lb 1._ 9.8: m .u_ .o memz m cowumem> eeceewwwcmwm :me: we Eem we memeem meme 2F EmFeepcmme< ememm>< :e peFmmeo ecm .Fe>ee .xem we meeewwm mew emeF .mFF.e eFeeF 161 wmme. FoFFw. oFNoo. nmwwo.1 mmFoo.1 om< H we eeFm>1F eecmewwwcmwm Lemmm .epm mpmm m mpmwmm> IOU (i/h/l/ emmme><11mFeeme> pceeceeea .ELwF memmm mFFeo :wgpwz Lew mmeFec< :ewmmemmem Leeee>ez CF Emweepceme< ememe>< ece em< ceezpem ewzmcermFem esp mew pmeF .NNF.v mFemw 1111111 movmm. mFoFN.1 mFNoo. NOMNO.1 mwooo.1 om< F we meFe>1F Lemmm .epm epem m epmwmm> eeemerwcmwm 1eu //f/(/I mmmgm><11eFemwme> Fceeceemo .Emmw Lemmm mFFmo :wgpwz Lew mmech< :emeemmmm memepeo eF Emwemwceme< ememe>< ecm mm< :eezmem ewsmceFFmFex esp mew “mew .FNF.e eFeeF 111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111 vmmmN. mmmmo.F FeFoo. mmmFF. mmFoo. wm< F we esz>1F Lemmm .eum epem m epewmm> wecmewwwcmwm 1 8 l/// 162 mFmFm. FeONw. mvNoo. NFovo. moFoo. mm< F we esz>1F Lemme .epm epmm m mpmwme> meceewacmFm ou ememe><11mFemFme> pceecmeea .ELeF Lemmm mFFeu cwzpwz mew mwmmFec< :ememmmem mmmemewe :F EmFeepcmme< emmmw>< ecm mm< :mezpem ngmceFFmme esp Few pmmF .mNF.e ereF // wmmmw. mmva. oeNoo. FFNmo. FFFoo. wm< F we eeFe>1F memmm .epm epem m ememm> mesmerwcmFm eu ll/X/ ememm><11mFemFLm> pceeceemm .ELeF mommm mFFeo :wcpwz Lew mmeFec< cowmmemmem mmmzcme :F EmFeepceme< mmeme>< ecm em< :eezpem ermcermFem esp Lew FmeF .wNF.¢ eFemF f// mmNmm. eNemm.1 NmNoo. FONoF.1 NFNoo.1 mm< F we Lemme .epm mmmm m epmwme> eucmerwcmFm IOU ; 163 onmm. ommmm. mmFoo. owmmo. mmooo. mm< F we ezFe>1F memmm .epm epmm m eemme> eecmewwwemwm 55 mmeme><11ereme> mceeceeea .EmeF Lemme mFFmo :wspwz mew mmech< :ewmmemmem meme :F Emweepceme< emmmm>< use em< :eezwem chmcereFem esp mew FmeF .mNF.e eFeeF NNmmo. vemmF.N1 owFoo. mNFMN.1 ammoo.1 wm< F we esz>1F Lemmm .epm mpwm m ememm> weceewwwcmwm 5 ememe><11eFemme> Fceeceemo .ELeF Lemme mFqu :wcpwz Lew mwmmch< :ewmmemmem Am: :F Emweepzeme< ememw>< ecm em< :eezpem ewgmceFFerm mew mew pmwF .mNF.¢ eFeeF Fowwo. mmmNF.F1 mONoo. mewF.1 qmmoo.1 wm< F we szm>1F Lemme .epm epem m euewme> meceewwwcmwm . IOU emmme><11eFemFLe> erecmeeo .ELeF Lemmm mFFmo :wcpwz Lew mwmmch< :ewmmemmem mee< :F Emweepceme< ememe>< ecm em< ceezpem ewcmcewmeem mew mew pmeF .FNF.¢ eFeeF FONoo. Fmeo.1 emooo.1 wm< F we emFe>1F Lemme .epm mumm m mmmwme> eecmewwwcmwm / >3 164 11111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111 Fmeem. mNmNN. FeFee. N mmNee. eeFeemFe me Fe>ee me xem NFFNe. memmm. eemee. N mNFFe. eeFmemFe me Fe>ee eeeme. mmmFm.m FeNme. F FeNme. eeFeemFe me xem NmeFe. emFeF. Fmeee. N Nmmee. Fe>ee me xem emmem. eeFee. Feeee. F Feeee. eeFemmFe emmee. Nmmmm.m NNeNe. F NNeNe. FNV Fe>ee ememm. eFeee. eeeee. F eeeee. FFV Fe>ee eFNeF. eFm m.F eemFe. F eemFe. xem n. we wee: m .L .Q meme: m :ewpmwmg musequchwm see: we Eem we 8.58 5h!) 32:: Lew Emweepcemee. mamme>< :e FermE ecm .Fe>e._ .xem we mpeewwm Lew pmmF .omFé eFemF 165 ;ex and district of residence. This data is presented in Tab1es 11, 4.132, and 4.133. The fo11owing conc1usions were drawn from data: 1. Fema1es who resided inside of the Davison Schoo1 District missed 1ess time for i11ness than fema1es who 1ived outside of the district for each year studied. . Ma1es who 1ived inside of the district missed more time for i11ness than did ma1es who 1ived outside of the district for each year studied. . Fema1es were absent more than ma1es for i11ness during every year studied except 1977-78. . Fema1es were absent 3.2 percent of the time for i11ness, whi1e ma1es were absent 2.8 percent of the time. . Staff members who 1ived inside of the district missed more time for i11ness than staff members who 1ived outside of the district for each year studied except 1976-77 and 1980-81. However, the mean absence time was s1ight1y greater (2.94 percent vs. 2.93 percent) for those who 1ived outside of the district over the tota1 six years of this study. Persona1 Leave Tab1e 4.134 shows that there was no significant interaction n sex, 1eve1, or district of residence and staff absenteeism for 31 1eave time. 6 6 1.. uvmuuwFo mmme. emme. mmFe. emme. mmme. emme. mmme. emme. mmme. mmme. mmme. mmme. memmeeo uomuummc mmme. mmme. mmme. emme. mmme. mmme. FmFe. eeme. mmme. mmme. mmme. emme. memmcm meme. emme. meme. emme. mFme. eFme. mmme. mmme. eeme. mmme. mmme. emme. mqce .eew :emm 4Mmm14wmm mmmw 4wwm1nmww NMmm 4Mmm1neem mme wwwm14eem :eaz .>mm1uwmm cum: mm1emmF mF1mmwm mF1FFmF mwummwm wamFmF mm1emmm euceewmmm we pewmpmwe ecm xmm he czeo cememm ems: mmeeFFF Few Emweepcemm< we emmmcmemee .FmF.¢ wFaeF emme. cm®2 mmNo. :mw2 eemm. Feuoe mmmm. Fauoe memu Fm1emmm mmme. mm1emmm mmme. mm1mmmm meme. mF1mmm2 meme. mF1FFmN mmme. mm1mmmm mmme. mm1eFmF mmme. Fm1emmm mmme. em1mFmF meme. eF1mme mmme. mF1vmmF emme. mF1mme momuummo wcmwuzo uomuummo 06mmcH v/ mmme. new: mmme. sew: meme. ceoz mmme. :moz mmme. see: mmme. saw: as Nmee. maeoe emme. Feeoe meme. Feeoe mmme. quoe eeme. quoe emme. Fmeoe .1. 11.1 . 11111 1.11.11 111I1ll 1 111.11.: emme. .2 emme. .m emme. .2 emme. .m emme. .2 mmme. .m emme 2 emme. .2 mmme. .2 mmme. .2 meme. .2 mmme. .2 “.025me $39.20 uomuummo oumwuso moan—ammo mgmuso uomuummc ocmmusc uoHuummo mammuzo momhummo mgwuzc VFNo. :moz memo. :60: meo. :60: mmme. :moz memo. :mmz vmmo. cam: meme1 memos mFee. Feuee mmee. Feeoe meme. Feeoe mFee. memos meme. Fence meme“ “2 emme. .2 wwmmq .2 emme. .e mmmea .2 emme. .m omNo 2 NNMO. .2 vmmo. .2 mmme. .2 Name. .2 Name. .2 uuFuemme oemmem momuemee wemmem mommemme oemmem uuFuemFe eemmcm mummemme eemmcm momeumme oemmem Fm1emmF mF1mmwM mNnNNmm Mmremmw mM1mFmF mmmwmwm HUFLHWFD 5:6 168 ommo. FwNo. moNo. meo. :mwz meN. QNFF. FFwF. owFF. FmFOF mmme. Fw1ommF FmNo. Fwnome mmNo. Fw1ommF mmNo. quome ommo. mF1meF mmNo. mmanmF NNmo. mF1meF NNmo. mF1meF ommo. wmnmmmF mmNo. wF1FFmF emme. wFunmmF emme. wF1FFmF mmme. FF1oFmF ocNo. FF1mFmF mmNo. FF1mFmF moNo. FF1©FmF mmme. mF1mFmF meo. ©F1mFmF NONo. oF1mFmF FmNo. mF1mFmF mmme. mF1¢FmF oFNo. mF1¢FmF mFNo. mF1¢FmF NmNo. mF1¢FmF eeFeemFe eewmeee FeFeemFe eeFmeF meFmsee Lew Emwmemcmmm< we mmmpcmemee FemeF :mez eeFeemFe eeFmeee eememFe eewmeF mesz mew Emwemuceme< we emepceemee FmpeF :mmz mmeeFFF mew pewmpmwo eee xem me Emwmemceme< we emepceemme FmpeF :mmz .mmF.v anmF 169 NNmFm. mmeF. meeee. N FFeee. eeFeemFe me Fe>ee me xem mmmmm. NFFFe. eeeee. N Feeee. eeFeemFe me Fe>ee mmemF. mFmFe. meeee. F meeee. eeFeemFe me xem eemmm. mmmee. meeee. N eeeee. Fe>ee me xem memNm. emmee. eeeee. F eeeee. eeFmemFe mmFmN. mmNFe.F Fmeee. F Fmeee. FNV Fe>e2 eeFFN. meemF.F meeee. F meeee. FFV Fe>ee mmFFm. Femme.F Neeee. F Neeee. xem 2 we 2 emmeem .2 .e memeeem :ewpmwmm> mesmewwwcmwm see: we Eem we memeem e>ee2 Fecemmee mew EmFeeucemm< ememm>< :e pequmFm ecm .Fe>em .xem we mpeewwm Lew pmeF .emF.e eFemF 5...... .. if: 170 Schoo1 Business Tab1e 4.135 i11ustrates that there was significant difference en the absenteeism rate of high schoo1 staff members for schoo1 ess purposes when compared to e1ementary and junior high schoo1 members. The researcher de1ved more deep1y into the statistica1 for staff absence for schoo1 business purposes. This information asented in Tab1es 4.136 and 4.137. The fo11owing conc1usions are ad from this data: 1. E1ementary teachers missed the greatest amount of time for schoo1 business in on1y one of the six years studied and missed the second greatest amount of time during each of the other five years. 2. Junior high schoo1 staff members were absent for schoo1 busi— ness the greatest amount of time during one of the six years 1 studied, tied for second greatest amount with e1ementary teachers for one year, and were absent the 1east amount of time for four of the six years studied. . High schoo1 teachers missed the greatest amount of time for schoo1 business during four of the six years studied. They were absent for schoo1 business the second greatest amount of time for one year and missed the 1east amount of time for one year. . High schoo1 staff members were absent for schoo1 business the greatest amount of time (.0048) over the entire six years studied, e1ementary teachers took the second greatest amount 171 .11111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111 mNmFm. mmemm. mmeee. N eFeee. eeFeemFe 2e Fe>e2 me xem Femmm. mFFee. Neeee. N meeee. eeFeemFe 2e Fe>e2 Neme. FmNNe. Feeee. F Feeee. eeweemFe me xem mmeNF. meeFF.N mFeee. N emFee. Fe>e2 me xem emmem. FNeee. eeeee. F eeeee. eewemmFe mmmee. meeNe.m mmNee. F mmNee. FNV Fe>e2 mFFFN. eeme.F emeee. F emeee. FFV Feeee mFmeF. mmmeF. eeeee. F eeeee. xem 2 we meme: m Cowpewmm> eecmewwwzmwm see: we 53m we memeem mmeCFmem Feecem mew Emwemmceme< emm2e>< :e FeFLFmFQ ece .Fe>em .xmm we mpeewwm Lew pmmF .mmF.e eFemF 172 Hmoo. mvoo. oHoo. oHoo. mmoo. Hmoo. vmoo. mNoo. .>oe .tem mmms Fm1emmm o m o moo. moo. moo. . >00 F1mFm Nooo. «moo. oooo. wooo. cams llllllllllllllllfllll onoo. wmoo. mmoo. ovoo. emoo. NHco. vmoo. NHoo. mmoo. Avoo. mmoo. omoo. omoo. mmoo. omoo. vmoo. .>oe .eom mmmm mF1FFmF .>mm14eum cam: FF1oFmH cmoo. vaoo. mmoo. «moo. avoo. ofioo. mmoo. FHoo. awae .emm ewe: oFImFmH mooo. onoo. avoo. mwoo. vvoo. mmoo. omoo. ovoo. .>OQ .wum :m02 mhlvhmfi Fe>e._ .3 use mmeew .3 :28 :exemm 2222 $9.55 Feecem Lew meceme< we mmme.:eemfl Hoozom 2mm: mem:mm Hoo:om :mm: momcso >umucwEon :Omumasmom oumucm ~02 .omF.¢ aneF 173 5 weoo. ONoo. mmoo. :mwz FwNo. FNFo. NFNo. FmFOF meoo. oFoo. FNoo. Fo1ommF Nmoo. wmoo. oooo. mF1meF omoo. NFoo. Feoo. wF1FFmF oqoo. NFoo. mmoo. FF1oFmF oFoo. wNoo. oFoo. oF1mFmF oFoo. mNoo. mNoo. mF1¢FmF epmm mecemm< :emz mpmz wecmme< :eez mpem mucmmm< :eez LmeF Feecom new: Lewcmm Feegem Law: mchee mmmpceEeFm Fe>mm me czeo cexemm 2mm: meepm exp we mmmeF me mew mew mmecwmem Feegem Lew eeceme< we mcmmz we mewmeesem .FmF.e eFemF of time (.0035), and junior high schoo1 staff members were absent the 1east amount of time (.0020) for schoo1 business during the six—year period studied. Dock Days Tab1e 4.138 i11ustrates that there was no significant re1ationship etween sex, 1eve1, or district of residence and staff absence for dock ays. Tab1e 4.139 shows that there was a significant re1ationship between 3x and staff member absence for bereavement. Tab1e 4.140 i11ustrates iat fema1es used over twice as much time for bereavement as was used 1 ma1es during the six years studied. Davison Education Association Business Tab1e 4.141 i11ustrates that there was no significant re1ationship 1tween sex, 1eve1, or district of residence and staff absenteeism for E. A. business. The Significance of F exceeded a (a1pha) = .05 for ery variab1e tested. Jury Duty Tab1e 4.142 indicates that there was no significant re1ationship ! tween sex, 1eve1, or district of residence and staff absence for jury j :y. ' 1ts for Re1ationship Between Age and 1rage Absenteeism by Reasons for ence Regression ana1ysis was used to test for any significant re1at10n p between age and average absenteeism by reasons for absence The nificance 1eve1 at which these tests were conducted was set at a1pha) = .05. 175 oeoqm. Nmmoo. ooooo. NFooo. Fowcumwo An Fw>w2 >2 xwm eNNeF. FemeF. Feeee. Hmmmmw FeNmN. eFemm. mmmmma 2 we mesmewwwcmFm mommm. FmowF. mmFFv. ommov.m momoF.F «Nmoo. waom.m moooo. Foooo. eoooo. mmooo. FFooo. ooooo. woooo. r—l—‘l—‘P—NF—NN ceez ewe: m .2 meme: m Feeee. eeFeemwe me Fesee Feeee. eewwmmwe me xem meeee. Feeee me xem mmeee. pewtemwe FFeee. FNe Fe>ee eeeee. AFV Fmeem mmeee. xem :ewpmwwm> we Eem we weweem mnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnHnnnnnnnnnunnnnnnnnnnnnnnnnnnnunnnnnnnnnunnnnunnnunnnnnnnnnnnnnm pceEe>me2em Lew Emewpcmme< mmewm>< :e pewwpmwo ecm mmvmw. wFomF. «Fooo. wNooo. Fowwpmwo me Fw>w4 An xwm mmva. Fquo. ommNm. F¢Nom. oowNm. oFomm. eoome. mmomo. momoF. eFNmF. mme¢. NoFoq. mwmoo. mmoFo. 2 wo 2 euceewwwcmwm omooo. NFooo. mFooo. mmooo. Fmooo. ooooo. Feooo. r—r—P-P‘Nr—NN LD— :_D_UUJ._U03:. JD!.J... ..1 11, xem we meeewwm mew emew .mmF.e eFeeF eeFee. eeFeemFe me Fe>e2 NFeee. eewwemwe me xem mNooo. Fw>m2 an xwm mmooo. pewwumwe Fmooo. FNV Fm>em ooooo. FFV Fe>e2 Fvooo. xmm CowuowLo> see: we Eem we eemzem mzm: gee: 1 1 1: MNOO. NHOG. :GwS mmao. whoa. HmuO? mHoo. mooo. Holommd mmoo. VHOO. mhlmhmH mNoo. hfioo. mh1fihmd NHOO. hooo. hhlobmH ONoo. omoo. mhlmhoH 6 Fmee. eeee. :1..me 7 ['1’ 1" 11 oHeEom er: Nvoc. wHoo. H000. mmoo. wmoo. mNoo. omoo. hdoc. Hmoo. omoo. coco. HNoo. wHwEwh mace. mooo. mmoo. VFoo. mvoc. haoo. HNco. Fooo. Nvoo. omoo. «moo. mooo. me2 :OMumHSQOm cho. Mdoo. ovoo. vmoo. ovoo. mmoo. wmoo. Nfioo. owoo. oNoo. mvoo. MNoo. wuducm H02 .>0D .oum 2mm: .>wo .Cuw moo: HNMQ .oum Mao: d>oo .mww :mwz .>oo .oum 2mm: u>oo .oum :dm: me1emm1m. mF1eFmF eF1Fme 1F1F1eFmF em1mFmF 21:3. xwm %o :30: :szLD e:vED>UU_U3 _>_ J):J>1: .1 1311 177 eemFF. FeeFN.N eNeee. N eeeee. eeFeemFe 2e Fe>e2 2e xem NeNmF. eemmN. meeee. N meeee. eewemmwe me Feeee mmmmN. emFFm.F NFeee. F NFeee. eeFeemFe me xem emNmm. eemem. meeee. N FFeee. Fe>ee me xem Feeem. Nmemm. meeee. F meeee. eewwmmwe eeeFm. mmeme. eeeee. F eeeee. FNV Fe>e2 eNNeF. eNemF.N mNeee. F mNeee. FFV Feeee mNemm. ememF. Feeee. F Feeee. xem 2 we 2 emmeem .2 .Q mewmecm :ewpewwm> eecmuwwwcmFm :me: we Eem we eeweem memo meme Lew Emwwepceme< emmwe>< :e Fewwmeo eem .Fe>e2 .xem we mpemwwm Lew pmmF .NeF.¢ mFemF eNeee. mFFFe. Feeee. N Neeee. Feweemwe me Fe>e2 me xem ONmme. emmmm. Noooo. N moooo. mewwpmwo mm Fe>e2 meemN. moFmF.F moooo. F moooo. Fewwmmwo me xem emeNe. oFoem. moooo. N moooo. Fe>e2 mm xmm NFmNe. FFemN. Foooo. F Foooo. pewmpmwo emmFm. memoo.F moooo. F moooo. FNV Fe>e2 FmeF. eemNN.N 20000. F Foooo. FFV Fe>wm meNF. FoFem.N 20000. F Foooo. xem 2 we 2 emmeem .2 .o mesmeem cowpmwwm> eecmewwwemwm see: we gem we moweem mmmcFmon :onwFuomnI :D_JUJJJJ ->,n >5) n-» ...11 178 Tab1es 4.143 through 4.149 i11ustrate that there was no significant re1ationship between age and average absenteeism for i11ness, persona1 1eave, schoo1 business, dock days, bereavement, Davison Education Associ— ation business, or jury duty. Percentage of Absence--Genera1 Statistics Age Group--Six-Year Tota1s The percentage of absence of staff members of the Davison SchooTs, when divided by age grouping, is depicted in Tab1e 4.150. The mean rate of absence for the six years studied was 2.94 percent. Staff members vere divided into groupings covering ten-year increments from the twenties through the sixties. Percentage of absence ranged from a 10w )f 1.5 percent for those teachers in their sixties to a high of 3.3 per- :ent for teachers in their twenties. Staff members in their thirties 1ere absent 3.01 percent of the time; those in their forties 2.77 percent 1f the time, and staff members in their fifties were absent 3.12 percent f the time. 11ness--Six-Year Tota1s by Leve1 A summary of Davison professiona1 staff member absence for i11ness hen broken down by 1eve1 for the six years studied is shown in Tab1es .151 and 4.152. High schoo1 staff members missed the 1east amount of ime for i11ness during a11 six of the years studied. Junior high schoo1 1d e1ementary staff members each missed the greatest amount of time for 11ness during three of the six years studied and missed the second ‘eatest amount of time for the other three years. 179 11111111111111I11I1111111111I1111111111111111111111111111111111111I111I1I1111111111111111111111111111 vvow. moooN. mNooo. NoNNo. eeeee. em< F we e3Fe>1F wemwm .epm epem m muceowwwcmFm mpmwwm> IOU HHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH eme2e><11eFemF2m> pceuceeeo .ELmF 2022M mFFwo cwcpwz Lew mwmmFec< :ememLmem mmecwmzm Feesum wow Emweepcemm< wmeme>< wee wm< :wmzpem ewzmcewmemm e22 Lew meF .meF.¢ eFemF 11111111I111111111I1111I1111111111111111111I11111111111111111111111111111111111111111111111111111I FFmom. Nvmmm. Fmooo. memme. eFeee. em< ewee m F wo msFm>1F memwm .ewm eeemewwwcmwm mpmwwe> -8 (51/ emm2e><-1eFemee> pceecmmen .ELeF Lewwm mFFeo :wspwz mew mmeFec< :omemmem e>me2 Fecem2m2 wow Emwewpcmmm< mm mww>< use em< :ewzpem ewcmceFFeFem esp Low pmwF .eeF.¢ anmF oooFm. ooomm.1 vNFoo. MNFmo.1 FFFoo.1 wm< F we szm>1F Lemme .epm mwmm m epmwwe> meeeewwwzmwm eo mmm2w>211e_ee_ce. e:u::U2u: o__..J. .3...’ 180 mmewN. FFFFo.F ooooo. FwFFF. moooo. mm< F we weFm>1F Lemwm .epm mpem m epeF2e> mecmuwwwcmwm eme2e><11anere> Feweceewo ELeF Lemme mFFeo :wzpwz Lew mmeFec< :ewmmwmmem .mmmcwmzm :ewweweemm< :owpeueem :emw>mo Lew Emwwmpcmme< eme2e>< use em< :ewZFem ewgmceFFerm mew mew pmeF .weF.e eFeeF /’( woFom. mmmoo. mFooo. ewNFo. oFooo. wo< F we meFm>1F Lewmm .ewm ewmm m epmwmm> woceewwwcmwm 10o uHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHMHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH ememe><11eFemF2m> pceeceeea .ELmF Lewmm mFFwo cwspwz mew mwmmFme< :ewmmwwmem memem>ee2mm Lew Emweepcemm< emm2m>< 22m em< :eezuem ermceFumFem esp Lew pmmF .FvF.¢ mFeeF // woon. eeFNN. Nvooo. omvNo. oFooo. mm< F we eeFe>1F Lecmm .epm mpem m mme2m> eeceewwwcmwm -ee 55 OmflLw> ...:DDZDlDD J: _U_ .D . .J .1. . 1.11. 1 F‘Ty“ 181 mmmFm. mmooo.F mFooo. FFmoF. mFooo. mm< Lemmm .epm eumm m epmwwe> muceowwwcmwm 10o emewm><11eFeew2m> pceeceeeo .ELmF memmm mFFmo :wzpwz mew mmech< :ewmmwwmmm Amen meme Lew Emwmepceme< emm2m>< ecm mm< semapem ewcmcewweFem e22 Lew ummF .meF.v mFemF 182 ennui-llllilar111 m e mmme. me1ee mom/F m emme. mmme. mm1em mmmm e mmme. mmme. mm1em mom< m mmme. meme. mm1em mmm< m meme. mmme. mm1em mama :emumH5202 I mafio. voNo. mumucm How xcmm .>Qo .omw new: meme» xmm mmmezm mom momemme00 .Uum EGG: .>QD .Uam 2mm: .>0Q .Uuw :mwz illllllfl m1m 1111111 1111111 1 mm uuuuv1111 me mF1Fme FF1eme em1mme mm m mmeeF 2me>1xwm11eeemw em< me czea :exewm :e mmlow m00< mmlom mmm< owlow mead mmtom mmmd mmloN mmw< :OmummsmOm mumucm mom mmme. mmme. .meme. mmme. emme. eeme. emme. meme. mee. meme. mmme. meme. moozom 2mm: acesom meme. :8. mmme. emme. meme. emme. emme. meme. :3. meme. mmme. emme. 2mm: ...omcse 3 e . . . mm mme mmme meme. emme. mmme. meme. meme. mmme. mmme. mmme. mmme. mmme 3355mm :Omummsmom meme. . . . cm no.2 . mmme meme m.eme. mmme. mmme. mmme. eeme. mmme. mmme. mmme. mmme ammo .>wo .wum mm11 411114111 11 111111111 dalmlow1m1w. w: >wD Uuw EGG: .>OD .Uuw “m2 ..1>®1D.1mvu1w ww01: flaw Emmi u>00 .QUW ENG: 111. .1- 111111 11111 mF1mme 212mm .F1F111e1m1m1m1 1e1m111m1wm mF1§mm mFmpe 2m 1 1 F e> xwm 1Fe>e2 me ecm mwmmw me czeo sexemm ewe: mmecFFm mew eeceme< we mmmmceowe2 .FmF.e eFeew 184 mmNo. mFmo. meo. cemz mNmF. meF. FomF. meeF mmme. VFNe. mFmo. FwIOmmF NMNe. emme. emme. mF1mFmF eeNe. emme. meme. mF1FFmF meme. mmme. FmNe. FFeFmF mowo. COMO. mmmo. mulmnm— meNe. emme. mmNe. mFimF Feemem new: gee: Feecem saw: mewcee :mmz 22mmceEmFm 2mm: mmeF WPMHOH me>lem .Nm~.¢ wrflmh 11Fw>w4 An czoo :wxogm 20:3 wwmcFFH Lew Lom> xfi meow: we >onEom 185 E1ementary teachers missed the overa11 greatest amount of time for i11ness (3.18 percent) for the six years studied. Junior high schoo1 teachers missed the second greatest amount of time (3.15 percent), and high schoo1 teachers missed the 1east amount of time for i11ness (2.55 percent) for i11ness for the six years. Days of the Week--Six—Year Tota1s Absenteeism tota1s for Davison staff members for i11ness by days of the week are i11ustrated on Tab1e 4.153. Absenteeism ranged from a high of 3.3 percent on Mondays to a 1ow of 2.7 percent on Wednesdays. Teachers were absent 3.01 percent of the time on Tuesdays, 2.73 percent of the time on Thursdays, and 2.99 percent of the time on Fridays. Months of the Year--Six-Year Tota1s Percentage of absenteeism by months of the year and six-year tota1s are contained in Tab1es 4.154 and 4.155. Tab1e 4.154 presents the mean absence rate for the ninety—six subjects who were emp1oyed for the entire six years studied. Tab1e 4.155 contains the mean absence rate for a11 three hundred fifty-seven staff members studied. Tab1e 4.154 shows February to be the month when the greatest percentage of absences occur (3.7 percent), and March to be the month when the second greatest per- centage of absences (3.4 percent) take p1ace. Tab1e 4.155 i11ustrates hat March at a 4.9 percent absence rate is the month with the greatest eacher absence, whi1e February is second at 4.7 percent. Both tab1es how September to be the month with the 1east amount of teacher bsenteeism. 186 11 11111111111111111111111111111111 m mmme. mmme. meme. meme. meme. meme. mmme. meme. mmme. ,mmme. emme. mmme. mmme. meme. meemmm m mmme. mmme. meme. mmme. meme. meme. meme. mmme. meme. mmme. mmme. mmme. emme. emme. mmemueme m mmme. emme. mmme. eeme. mmme. emme. mmme. mmme. emme. emme. mmme. meme. emme. meme. mmemmcewz m mmme. meme. mmme. mmme. mmme. mmme. emme. mmme. mmme. meme. emme. mmme. mmme. eeme. meemase m meme. emme. emme. mmme. meme. mmme. meme. meme. meme. mmme. meme. mmme. emme. meme. mweeoz 0:52 .>oo. tum :20: $619 . cum :ma: . >09 . cum new: . >®e . Fe... m :20: FJFMQ . cum cam: . Ewe . Cum. coo: Sue . «cum :mwz wwwmwmwm mm1eemm mw1emmm mF1Fme FF1eme em1mwmm mF1mme 2mm: esp we mmmo me Emweepceme< we emmmcwewm2 .mmF.e ermF o ave. 5 five. N wvcm A mmo. (’1 «mo. 187 If} N Ln 0 w hvo. am fine. JMMm .cum xcmz omo. wmwo. vmo. nmo. mmo. EMU: mane? umm>lxmm mmo. VHO. va. QHO. moo. HVO. NMO. OMO. NNO. QQO. hvo. HmO. OVO. MNO. hmO. mMO. ONO. meo. emO. va. hmO. mmO. me. VMO. mmO. hvo. MMO. mMO. ONO. moo. va. NNO. th. Nmo. mvc. NOO. NMO. HwO. who. va. va. ONO. VVO. HMO. NOO. HMO. th. hvo. ONO. OHO. .>03 :mm: .>wo cam: dwmm .Uum .Uuw .Cum meleeem NMHmem MMH mewnsz eeepm em Lee Lew> esp mo mcmcoz he Emmwmpcwme< mo wmepcmuewe mmo. hmo. vmo. ovo. ovo. mmo. mmo. nmo. moo. :moz sham NMO. has. even eme. hmO. mmo. mvo. vmo. mvo. Nmo. «mo. NMO. vwo. mmo. mmo. MNO. mmo. VNO. ONO. moo. .>ma mmwm .Uum MMHMMNM mvo. omo. Nmo. owe. Nvo. mmo. Ave. wmo. coo. ¢¢o. wvo. «mo. wmo. Nmo. mmo. mmo. «mo. mmo. mmo. ONO. .>wn :dwz .wuw mmnmmmm mmo. v90. wmo. we. omo. .>wo .cum mp! nmo. wcsn mme. mm: eme. mmuee mme. comm: Nmo. >um:pnoh mvo. >um::mn mmo. umnEwooo mmo. umnE®>oz «mo. uwQOuuo cmo. umaamumwm :mwz cucoz chad .vmm.¢ mmmep 188 m OMOMO. mmMMO. mwwNO. OVHMO. OwwMO. NHMNO. NVOMO. 025% v wvwvo. vNMVO. hOmvo. mahvo. wOOQO. mmva. OvmmO. >ME h BOHVO. OVOQO. ovaO. memO. mwwmo. OVNMO. HomVO. HMHQ< A mdmvo. mmmmo. mdme. mmomo. evomc. Omva. mOHmO. LOMGZ N HOth. HvaO. mOva. MOOVO. Nomvo. memO. nmvvo. humsufiwh m mewvo. MOOMO. vwhmo. mNHmO. mmmmc. mmva. «OOOO. >HMDEMO m VBOVO. mwmmo. NmOmO. hvovo. Hehmc. ONNmO. HOOMO. HOQEOUOC w Nmmvo. OONmO. mmomo. OVHMO. Amwvo. OBOVO. meVO. HQDE0>OZ e eveme. ememe. mmmme. memme. mmmme. meeme. «meme. umnouoo nmml mmmme vemme. mmeme. eeeme. meeme. veeme. «emme. uwnswuewm xzmm 5.5: :5: 5.5: Meme. 3 saw: aml: meeoe pawm-xmm me-eeem emnemem emlmmem mmummmm mmnmmmm em-mmem Luce: meweEmz eeemm mmm Lee Lem> esp mo mgpcoz me Emweepcwmn< eo mmemcm0Lwe .mmm.e mmeem 189 Percentage of Absenteeism by Year--Six Year Tota1s The tota1 mean percentage of absence for Davison professiona1 staff members during the six years of the study is i11ustrated in Tab1e 4.156. The percentage of absence ranged from a high of 3.18 percent in 1977-78 to a 10w of 2.66 percent during 1976—77. 1978-79 ranked number two for the amount of teacher absence (3.04 percent), 1975-76 ranked number three (2.97 percent), 1980-81 ranked number four (2.83 percent), and 1974-75 ranked number five (2.81 percent). Summary An experimenta1 design was used to determine whether or not informa- tion and statistics presented by the researcher to the Davison Schoo1s' orofessiona1 staff cou1d bring about a change in the attitude of staff nembers towards the use of 1eave time. The response of the majority of :he professiona1 staff to the staff—1ine information presented by the esearcher was to ”remain neutra1”. The term ”treatment” is used to refer to the process wherein the esearcher met with the professiona1 staff and shared statistica1 nformation with staff members regarding teacher absence in the Davison choo1s for the schoo1 years 1974-75 to 1978-79, as we11 as research nformation on the educationa1 effectiveness of substitute teachers. The term "treatment effect“ refers to whether or not, in fact, 1ere was any effect or change in the rate of professiona1 staff absen— eeism during the 1980-81 schoo1 year. The researcher tested to find out whether or not there was a sig- ficant interaction between sex, 1eve1, or district of residence of 190 e meme. meme. m meme. eeme. m mmme. emme. e meme. eeme. m meme. meme. e $5. 58. xeem .>wn .epm new: mmemem Lee>-xmm-ueem> me Emmmemewme< me mmemeeoeee mwuowmm mmnwnm— mnumnm— mmuommm mmlmnm— mmuvmm— Lem> .ee_.e emeem on Schoo1s‘ professiona1 staff and the treatment. This test was cted for days of the week, months of the year, and reasons for ce. Repeated measures ana1ysis of covariance with measures of ntage of absenteeism repeated over six time periods was used. ignificance 1eve1 at which these tests were conducted was set at pha) = .05. Ana1ysis of variance was a1so used to determine whether or not: 1. There was a significant re1ationship between age and the effect of the treatment. 2. There was a significant treatment effect. These two tests were a1so app1ied against days of the week, of the year, and reasons for absence. Univariate F-Tests with ) D. F. were used to test these re1ationships. A summary of the resu1ts, further discussion, conc1usions based the resu1ts stated, and imp1ications for further research are ed in Chapter V. CHAPTER V SUMMARY, CONCLUSIONS, DISCUSSION, AND IMPLICATIONS FOR FURTHER RESEARCH Summary Teacher absenteeism is not a new prob1em. A distinct trend ard increased absenteeism by emp1oyees throughout the nation has ome apparent in recent years. Extensive studies of the prob1em of :her absenteeism have been comp1eted in Merrick, N. Y., Las Vegas, York City, Phi1ade1phia, Newark, Ohio, Chicago's north suburban 101s, Ca1ifornia, I11inois, and Indiana. The resu1ts in every y demonstrate a dramatic increase in teacher absenteeism. As addi- a1 days are made avai1ab1e to teachers through co11ective bargain- it appears that more of these days are being taken by teachers. Substitutes for teaching and non—teaching personne1 are a signifi- portion of the budget in each schoo1 district. In a suburban 1and schoo1 district of 12,000 students, in addition to $12,000,000 ldy committed to teachers' sa1aries, the board of education expended 100 during the 1979 ca1endar year for teacher substitutes. This was a1ent to a11 of the funds used to purchase educationa1 equipment year. In 1977, another major urban schoo1 system in Ohio expended 3,233, or $25.50 per pupi1. A Pennsy1vania study estimated the 192 sts for fi11ing vacancies with substitutes wou1d be in excess of 0,000,000 on a state-wide basis. The Davison Community Schoo1s spent 7,246.18 in payment for sa1aries of substitute teachers during the 80-81 schoo1 year. This amount is based upon a dai1y substitute te of $35.00. Substitute costs are high and increase every year. A dai1y rate $35.00 to $50.00 per day is not uncommon. Unfortunate1y, the educa— ona1 va1ue received for this expenditure is questionab1e. When a teacher is absent from the c1assroom, a substitute teacher provided so that the student 1earning can continue uninterrupted. t, a substitute teacher, no matter how qua1ified, cannot carry on are the regu1ar teacher 1eft off. A study conducted by the Metropo1itan Schoo1 Study Counci1 of Iumbia University conc1uded that substitute teachers were education- y ineffective. This study found that regu1ar teachers were twenty Ies more effective than substitutes in secondary c1assrooms. Even dent teachers were found to be more effective than substitutes. The purpose of this study was dua1. One purpose of the study was to secure accurate information rding the amount of 1eave time that Davison teachers have used over 'x—year period, 1974-75 to 1978-79 and 1980-81. Statistica1 informa- was gathered and compi1ed on teacher 1eave time used for various ons over that period of time. This information was then ana1yzed each staff member according to the fo11owing categories: age; sex; her they reside inside the Davison Schoo1 District boundaries or ide of the district; grade 1eve1 and subject area assignment; ementary, junior high schoo1, or senior high schoo1 teaching assign— nt; part—time and fu11-time teachers; days of the week that 1eave was ed, and months of the year that 1eave was used. This information was pi1ed and trans1ated into tota1 do11ar expenditures and per teacher enditures, as we11 as tota1 1eave days used and days used per cher according to the c1assifications out1ined above. The second purpose of the study was to use an experimenta1 design order to attempt to bring about a change in behavior on the part of ison teachers regarding teacher usage of 1eave benefits. A summary the statistica1 information described above was introduced to the ifessiona1 staff. An observation was then made as to whether the ff and the Davison Education Association responded with sponsorship rejection. This information was introduced to the teaching staff two methods. The first method was to make the information avai1ab1e to the ison Education Association. This was accomp1ished by a meeting with D. E. A. Executive Board on Tuesday, September 9, 1980. This is governing body of the 1oca1 teacher union. A presentation was oduced to show the extent of 1eave time used by Davison teachers. as hoped that the D. E. A. hierarchy wou1d sponsor the idea that thing needs to be done” to encourage staff members to use 1eave on a more judicious basis. The other approach to teachers that was emp1oyed was a persona1 to each of the bui1dings by the researcher, with a presentation at bui1ding staff meetings. The importance of the regu1ar c1ass— teacher to the student 1earning process was emphasized in each of staff meetings, as we11 as the meeting with the D. E. A. Executive 'd. The opportunity to observe the fo11owing behaviora1 responses present in each case: A. Sponsorship B. Approva1, but not sponsorship C. Neutra1ity D. Inactive opposition E. Active opposition The response of the majority of the professiona1 staff to the i 1eave information presented by the researcher was to ”remain ‘a1“. The term “treatment” is used to refer to the process wherein the rcher met with the professiona1 staff and shared statistica1 mation with staff members regarding teacher absence in the on Schoo1s, as we11 as research information on the educationa1 tiveness of substitute teachers. The term ”treatment effect” refers to whether or not in fact there 1y effect or change in the rate of professiona1 staff absenteeism J the 1980-81 schoo1 year. esu1t Summaries Five different tests were conducted on professiona1 staff absen- by days of the week, months of the schoo1 year, and reasons for e. I. The first test that was conducted was a test for modified nt effects or interaction between sex, 1eve1, and district of 196 dence and treatment on professiona1 staff absence for the fo11owing ons: Days of the Week 1. There was significant interaction between 1eve1 and the effect of the treatment on Mondays. 2. There was no significant interaction between sex, 1eve1, or district of residence and the effect of the treatment and professiona1 staff absence on Tuesdays or Wednesdays. 3. There was a significant interaction between 1eve1 and the effect of the treatment on Thursdays. 4. There was no significant interaction between sex, 1eve1, or district of residence and the effect of the treatment and professiona1 staff absence on Fridays. Discussion and Comments About the Resu1ts of Test Number One for Days of the Week The reason for the significant interaction between 1eve1 and the t of the treatment for Mondays was that the high schoo1 staff d the second greatest amount of time by 1eve1 for absence on ys during 1980-81 when they had missed the 1east amount of time for :e on Mondays for the other five years that were studied. The reason for the significant interaction between 1eve1 and : of the treatment for Thursdays was that the e1ementary staff ‘ the greatest amount of time for absence during 1980-81, and that e on1y year of the study that occurred on Thursday. The junior choo1 staff a1so missed the second greatest amount of time for 197 ence on Thursdays during 1980-81. This was the on1y year out of six years of the study that this occurred. There was no significant interaction between either sex or trict of residence and the effects of the treatment for any day of week. Thus, on1y the two variab1es discussed above of the fifteen iab1es tested for days of the week proved to have an interaction h treatment effect. The overa11 conc1usion from the resu1ts of test number one on s of the week must be that there was no significant interaction veen sex, 1eve1, or district of residence and staff absence by days :he week. Months of the Year 1. There was a significant interaction between sex and the effect of the treatment for September. 2. There was no significant interaction between sex, 1eve1, or district of residence and the effect of the treatment and professiona1 staff absence in October, November, December, January, or February. 3. There was a significant interaction between district of residence and the effect of the treatment for March. 4. There was a significant interaction between 1eve1 and the effect of the treatment for Apri1. 5. There was no significant interaction between sex, 1eve1, or district of residence and the effect of the treatment and professiona1 staff absence in May or June. 198 Discussion and Comments About the Resu1ts of Test Number One for Months of the Year ________________________________________ There was a significant interaction by sex and the effect of the reatment for September because the mean absence for ma1es in 1977—78 as .0074 contrasted with .0015 for fema1es, and in 1978-79 the mean asence rate for ma1es was 2.6 percent compared to 1.6 percent for ema1es. The reversa1 of this condition during 1980—81 where the mean isence rate for ma1es was on1y 1.7 percent for September contrasted 1 2.4 percent for fema1es caused a statistica11y significant inter— tion with the effect of the treatment to occur. The reason why there was a significant interaction between dis- ict of residence and effect of treatment for March was the mean ofessiona1 staff absence rate in March dropped from 3.49 percent in 74-75 to 1978—79 to 2.83 percent during 1980-81. The interaction between 1eve1 and effect of the treatment in ‘i1 came about because the mean percentage of absence for junior high 1001 staff members during 1980-81 was 4.69 percent compared to 2.5 'cent for the first five years studied. There was on1y one significant interaction between sex and the ect of the treatment and that was for September. There was on1y one nificant interaction between district of residence and the effect the treatment and that was for March. The on1y significant inter- ion between 1eve1 and the effect of the treatment occurred during 11. Therefore, on1y three of the thirty variab1es tested under :hs of the year were found to have a significant interaction with effect of the treatment. 199 The researcher must conc1ude from the resu1ts of test number one months of the year that there was no significant interaction between , 1eve1, or district of residence and staff absence by months of the Reasons for Absence 1. There was no significant interaction between sex, 1eve1, or district of residence and the effect of the treatment and professiona1 staff absence for i11ness, persona1 1eave, schoo1 business, dock days, bereavement, or jury duty. 2. There was a significant interaction between sex and the effect of the treatment and staff absence for Davison Education Association business. Discussion and Comments About the Resu1ts of Test Number One and Reasons for Absence There was a significant interaction between sex and the effect of treatment for Davison Education Association business because on1y les that were studied used 1eave time for D. E. A. business during -81, where on1y ma1es studied had been absent for that purpose during ’irst five years studied. Since there was significant interaction in on1y one of the y-one variab1es tested, it must be conc1uded that there was no ficant interaction between sex, 1eve1, or district of residence and ffect of the treatment and the absenteeism rate of Davison profes— 1 staff based upon reasons for absence. II. The second test that was conducted was a test for interaction in age and treatment and professiona1 staff absence for the fo11ow- asons: 200 Days of the Week _______________ 1. There was no significant interaction between age and the effect of the treatment and professiona1 staff absence for any day of the week. Months of the Year 1. There was no significant interaction between age and the effect of the treatment and professiona1 staff absence for any month of the schoo1 year except January. 2. There was a significant interaction between age and the effect of the treatment and professiona1 staff absence for January. Discussion and Comments About the Resu1ts of Test Number Two and Months of the Year A statistica11y significant interaction between age and the act of the treatment and professiona1 staff absence for January eared because there were zero absences during the 1980—81 schoo1 " for staff members studied who were in their sixties. Reasons for Absence 1. There was no significant interaction between age and the effect of the treatment and professiona1 staff absence for i11ness, persona1 1eave, schoo1 business, dock days, bereavement, Davison Education Association business, or jury duty. Discussion and Comments About the Resu1ts of Test Number Two There was on1y one significant interaction between age and the :t of the treatment and professiona1 staff absence for the twenty-two 201 “iab1es tested. Therefore, the researcher had to conc1ude that there ; no significant interaction between age and the effect of the treat- 1t and Davison professiona1 staff absenteeism. III. The third test that was conducted was a test for treatment ’ect on professiona1 staff absence for the fo11owing reasons: Days of the Week 1. There was no significant treatment effect on professiona1 staff absence for any day of the week. Months of the Year 1. There was no significant treatment effect on professiona1 staff absence for any month of the year except January. 2. There was a signifiéant treatment effect on professiona1 staff absence for January. Reasons for Absence 1. There was no significant treatment effect on professiona1 staff absence for i11ness, persona1 1eave, schoo1 business, dock days, bereavement, Davison Education Association business, or jury duty. Discussion and Comments About the Resu1ts of Test Number Three There was no significant treatment effect on professiona1 staff ice for any day of the week or reasons for absence. The on1y sig- :ant treatment effect for the twenty-two variab1es tested was for 1ry. The researcher ana1yzed the absence statistics for the month of 1ry and can exp1ain the significant treatment effect on1y on the that the mean absence rate increased from 2.04 percent during 79 to 3.31 percent during 1980-81. 202 Overa11, there was no significant treatment effect on Davison professiona1 staff absence. IV. The fourth test that was conducted was a test for the effects of sex, 1eve1, or district of residence on professiona1 staff average absenteeism for the fo11owing reasons: Days of the Week 1. There was a significant interaction between sex by district and professiona1 staff absence on Mondays, Tuesdays, and Thursdays. 2. There was no significant interaction between sex, 1eve1, or district of residence and professiona1 staff absence on Wednesdays and Fridays. Discussion and Comments About the Resu1ts of Test Number Four and Days of the Week There was a significant interaction between sex by district and rofessiona1 staff absenteeism on Mondays, Tuesdays, and Thursdays ecause fema1e staff members who resided outside of the Davison Schoo1 istrict were absent 21.14 percent more than fema1e staff members 1iving n the district. Converse1y, ma1e staff members who 1ived inside of ie district were absent 31.28 percent more often than ma1e staff members 10 1ived outside of the district. There was no significant interaction between district of residence 1d professiona1 staff absence for the six years studied. P1ease refer 1 Tab1es 5.1 and 5.2 for statistica1 data regarding mean percentage of sence by sex and by district of residence for the six years studied. e mean percentage of absence for the entire popu1ation for the six ars studied was 2.95 percent. 203 ab1e 5.1. Percentage of Absenteeism Broken Down by Sex and District of Residence for 1974-75 to 1978-79 and for 1980-81 Mean Std. Dev. )r the Entire Popu1ation .0295 .0312 i1es .0275 .0302 Living Inside District .0298 .0311 Living Outside District .0227 .0271 3ma1es .0317 .0318 Living Inside District .0291 .0301 Living Outside District .0370 .0338 .b1e 5.2. Means of Percentage of Absenteeism by Age and by District of Residence-~Six-Year Tota1s Inside District Outside District Ma1es .0298 Ma1es .0227 Fema1es .0291 Fema1es .0370 Tota1 .0589 .0597 Mean .0295 .0299 204 Months of the Year 1. There was a significant interaction between 1eve1 and district of residence and professiona1 staff absence in September. 2. There was no significant interaction between sex, 1eve1, or district of residence and professiona1 staff absence in October, November, or December. 3. There was a significant interaction between sex by district and professiona1 staff absence during both January and February. 4. There was a significant interaction between 1eve1 and professiona1 staff absence in March. 5. There was no significant interaction between sex, 1eve1, or district of residence and professiona1 staff absence in Apri1. 6. There was a significant interaction between 1eve1 and district of residence and professiona1 staff absence in May. 7. There was no significant interaction between sex, 1eve1, or district of residence and professiona1 staff absence during June. Discussion and Comments About the Resu1ts of Test Number Four and Months of the Year There was a significant interaction between 1eve1 and district of Tence and professiona1 staff absence in September for the fo11owing HS: 205 a. E1ementary staff members who 1ived inside of the Davison district were absent twice as often in September as e1emen— tary staff members who resided outside of the district. b. Junior high schoo1 staff members who 1ived outside of the Davison district missed near1y three times as much work in September as those staff members 1iving in the district. c. High schoo1 staff members residing inside of the Davison Schoo1 District were absent over ha1f again as much in September as those staff members who 1ived outside of the district. There was a significant interaction between sex by district of idence and professiona1 staff absence during January. Staff members resided in the district missed 3.42 percent of the time for absence ’ng January, whi1e staff members 1iving outside of the district Led 3.31 percent of the time. Ma1e staff members who 1ived inside of district were absent 3.4 percent of the time, and ma1es residing ide of the district missed 2.12 percent of the time. Fema1e staff ers who resided outside of the Davison district were absent 4.5 per- of the time during January, whi1e fema1e staff members 1iving ie of the district were absent 3.44 percent of the time. Fema1e f members were absent a greater percentage of the time (3.97 percent) 19 Januarys than were ma1e staff members (2.76 percent). There was a1so a significant interaction between sex by district rsidence and professiona1 staff absence during February. Staff rs who resided outside of the Davison district were absent 3.79 . ‘1 206 cent of the time during February, whi1e staff members 1iving inside the district were absent 3.7 percent of the time. Ma1e staff .bers who 1ived outside of the district were absent 3.95 percent of time, and ma1e staff members 1iving inside of the district were .ent 3.42 percent of the time in Februarys. Fema1es who 1ived out- le of the district missed significant1y more time during Februarys 29 percent) than did fema1e staff members who resided within the itrict (3.97 percent). Fema1e staff members were absent 4.63 percent the time during Februarys, whi1e ma1e staff members were absent 59 percent of the time. There was a significant interaction between 1eve1 and professiona1 tff absence during March. E1ementary teachers were absent for the eatest period of time in March during the six years studied, junior 1h schoo1 teachers were absent the second greatest amount of time, 1 high schoo1 staff members missed the 1east amount of time during ‘ch for the six years studied. There was a significant interaction between 1eve1 and district esidence and average absenteeism during May. The interaction was ificant for the fo11owing reasons: a. E1ementary staff members who resided in the district were absent 2.6 percent of the time in May, and e1ementary staff members who 1ived outside of the district were absent 3.5 percent of the time. b. Members of the junior high schoo1 staff who 1ived outside of the district were absent in excess of twice as often 207 (6 percent compared to 2.7 percent) as were staff members 1iving inside of the district. . High schoo1 professiona1 staff personne1 1iving outside of the Davison district were absent on1y inght1y more (2.9 per— cent compared to 2.8 percent) than staff members who 1ived inside of the district. Since there was significant interaction in on1y five of the thirty riab1es tested, it can be conc1uded that there was no significant teraction between sex, 1eve1, or district of residence and professiona1 aff absence. Reasons for Absence 1. There was a signifitant interaction between sex by district and professiona1 staff absence for i11ness. 2. There was no significant interaction between sex, 1eve1, or district of residence and professiona1 staff absence for persona1 1eave. 3. There was a significant interaction between 1eve1 and profes— siona1 staff absence for schoo1 business. 4. There was no significant interaction between sex, 1eve1, or district of residence and professiona1 staff absence for dock days. 5. There was a significant interaction between sex and staff absence for bereavement. 6. There was no significant interaction between sex, 1eve1, or district of residence and professiona1 staff absence for —___7——=T__‘“V ‘7 ' 208 Davison Education Association business or jury duty. Discussion and Comments About the Resu1ts of Test Number Four and Reasons for Absence There was a significant interaction between sex and district of residence and professiona1 staff absence for i11ness. Fema1es who resided inside of the Davison Schoo1 District missed le§§_time for i11ness than fema1es who 1ived outside of the district for each year studied! Ma1es who resided inside of the district missed more time for i11ness than did ma1es who 1ived outside of the district for each year studied. Staff members who 1ived inside of the district missed more time for i11ness than staff members who 1ived outside of the district except for 1976—77 and 1980—81. However, the mean absence time was s1ight1y greater (2.94 percent compared to 2.93 percent) for those who 1ived outside of the district over the tota1 six years of the study. There was a significant interaction between 1eve1 and professiona1 taff absence for schoo1 business. High schoo1 staff members were bsent for schoo1 business the greatest amount of time during the six ears studied, e1ementary teachers took the second greatest amount of ime, and junior high schoo1 staff members were absent the 1east amount f time for schoo1 business during the six-year period studied. There was a significant interaction between sex and professiona1 taff absence for bereavement. Fema1es used over twice as much time r bereavement as did ma1es during the six years studied. There was significant interaction between on1y the three variab1es ntioned above and staff absence out of the twenty—one variab1es tested der reasons for absence. There was no significant re1ationship tween sex, 1eve1, or district of residence and average absenteeism. 209 V. The fifth test that was conducted was a test for re1ationship etween age and average professiona1 staff absenteeism for the f011ow- ig reasons: Days of the Week 1. There was no significant re1ationship between age and average professiona1 staff absence for any day of the week. Months of the Year 1. There was no significant re1ationship between age and average professiona1 staff absence for any month of the schoo1 year except May. 2. There was a significant re1ationship between age and average professiona1 staff absence for the month of May. Discussion and Comments About the Resu1ts of Test Number Five and Months of the Year There was a significant re1ationship between age and average staff sence during the month of May. The researcher discounts this particu- r finding. Since the re1ationship between age and absence every day the week and every other month of the year was not significant, the searcher fee1s that the re1ationship between age and absenteeism in y just happened by chance. This was the on1y significant re1ationship out of the twenty-two riab1es tested in Test Number V. There was no significant re1ationship between age and average senteeism. Reasons for Absence 1. There was no significant re1ationship between age and average professiona1 staff absence for i11ness, persona1 1eave, 210 schoo1 business, dock days, bereavement, Davison Education Association business, or jury duty. Conc1usions A. There was a significant interaction between sex and professiona1 taff absence for bereavement. Fema1es used over twice as much time for rereavement 1eave as did ma1es during the six years studied. Tab1e 5.1 shows that ma1es were absent a mean time of .0275 with standard deviation of .0312, and fema1es were absent a mean time of 0317 with a standard deviation of .0318. The difference between an bsence rate of 2.8 percent for ma1es and 3.2 percent for fema1es was ot significant. Thus, the research hypothesis that there is no significant differ— nce in the absenteeism rate between ma1e and fema1e teachers in the vison Community Schoo1s has not been rejected. B. The re1ationship between age and absence for every day of the ek and for every month of the year except May was not significant. b1es 4.91 through 4.95 i11ustrate the re1ationship between age and sence by days of the week. Tab1es 4.118 through 4.127 show the re1a- onship between age and absence by months of the year. Tab1es 4.141 through 4.147 indicate that there was no significant 1ationship between age and average absenteeism for i11ness, persona1 ve, schoo1 business, dock days, Davison Education Association business, jury duty. 211 Thus, the research hypothesis that there is no significant re1a— tionship between absenteeism and the age of teachers in the Davison Community Schoo1s has not been rejected. C. Tab1e 5.2 i11ustrates that professiona1 staff personne1 who resided within the boundaries of the Davison Schoo1 District were absent a mean .0295 of the time, and staff members 1iving outside of the district were absent a mean .0299 of the time. Rounding off these means indicate that both groups were absent approximate1y 3 percent of the time. There was essentia11y no difference in the rate of absentee— ism regard1ess of whether the staff member 1ived inside or outside of the Davison Schoo1 District. Thus, the research hypothesis that there is no significant differ- ence in the absenteeism rate of teachers who 1ive in the Davison Schoo1 District when compared to teachers who 1ive outside the district has not been rejected. D. There was a significant interaction between 1eve1 and profes— siona1 staff absence for schoo1 business. High schoo1 staff members ere absent for schoo1 business the greatest amount of time during the ix years studied (Tab1e 4.135), e1ementary teachers used the second reatest amount of time, and junior high schoo1 teachers were absent he 1east amount of time for schoo1 business during the six-year period tudied. Five different tests were done for absence by 1eve1 for each ay of the week, each month of the schoo1 year, and each of the seven asons for 1eaving the emp1oyment of the Davison Schoo1s. Thus, the ta1 number of tests run for 1eve1 was one hundred ten. 0n1y three of 212 these one hundred ten tests proved to be significant. The tests that proved to be significant were sex by 1eve1 for September, comparing e1ementary and junior high staff against high schoo1 staff (1eve1 2) for March and 1eve1 by district for May. Obvious1y, this is 1955 than 1 percent of the tests run by 1eve1. Thus, the research hypothesis that there is no significant differ- ence in the absenteeism rate for teachers in the Davison Schoo1s, regard1ess of whether they are assigned at the e1ementary 1eve1 (K—6), junior high 1eve1 (7-8), or senior high 1eve1 (9-12), has not been rejected. E. Tab1e 4.153 i11ustrates percentage of professiona1 staff absen— teeism by days of the week. Absenteeism by days of the week ranged from a high of 3.3 percent on Mondays to a 10w of 2.7 percent on Wednesdays. Tuesdays had an absenteeism rate of 3.01 percent, Fridays 2.99 percent, and Thursdays 2.73 percent. The research hypothesis that there is no significant difference in the absenteeism rate for Davison teachers based upon days of the eek has not been rejected. F. Percentage of absenteeism by months of the year and six—year ota1s are contained in Tab1es 4.154 and 4.155. Tab1e 4.154 presents he mean absent rate for the ninety-six subjects who were emp1oyed for he entire six years studied. Tab1e 4.155 contains the mean absence ate for a11 three hundred fifty~seven staff members studied. The range of percentage of absenteeism in Tab1e 4.154 is from a igh of 3.7 percent in February to a 10w of 1.3 percent in September. he range of percentage of absenteeism in Tab1e 4.155 goes from a high 4.9 percent in March to a 10w of 2.1 percent in September. 213 The research hypothesis that there is no significant difference n the absenteeism rate for Davison teachers based upon months of the ear has not been rejected. Discussion Review of the 1iterature indicates that one of the primary reasons or teacher absenteeism today is stress spread over a period of time, r teacher "burnout”. The exact period of time required for “burnout“ 0 occur is, of course, a high1y individua1 matter. Other causes of eacher absence are persona1 or fami1y i11ness, persona1 1eave days, nergencies, and a1coho1 and drug re1ated absences. Data gathered for the first five years of this study revea1ed hat Davison teachers used the fo11owing mean absence days per year: Sick days 7.565 days per year Persona1 days .923 days per year Schoo1 business .875 days per year Bereavement 1eave .334 days per year Dock days .173 days per year Jury duty .030 days per year D. E. A. business .029 days per year Mi1itary 1eave _ygll_days per year 9.940 mean tota1 absence days per staff member per year The review of the 1iterature shows that Davison teachers enteeism at 3 percent is sti11 1ower than a Pennsy1vania Sch001 214 Boards Association study that reported ”the annua1 mean teacher absence rate was 4.7 percent. On an operationa1 1eve1, the 4.7 percent absence rate trans1ates into approximate1y eight days of absence per teacher per year.”1 Data covering the first five years studied in this research showed that Davison teachers were absent an average of 9.94 days per year for a11 purposes. Joseph W. Lansom reported that, ”Two and one—ha1f mi11ion workers are absent each Monday-~that is four percent of the working p0pu1ation.”2 The preponderance of research indicates that teacher absenteeism is more preva1ent on Mondays and Fridays. This research on Davison teaching staff personne1 mean absence rates showed that Monday was the day of highest teacher absence, which wou1d coincide with the other research. However, Tuesdays had the second highest rate of absence rather than Fridays. Teacher absenteeism in the Davison Schoo1s was the third highest on Fridays, fourth highest on Thursdays, and the 1owest on Wednesdays. Some professiona1 staff members in the Davison district indicated to the researcher informa11y that they be1ieved that Wednesday and Thursday a1so tended to be the days of the highest attendance for students and were days ”in which the most meaningfu1 instruction cou1d take p1ace.” 1Teacher Absenteeism Professiona1 Staff Absence Report, produced and researched by the Pennsy1vania Schoo1 Boards Association, iarrissburg, Pa., October, 1978. 2Joseph W. Lansom. How to Reduce Emp1oyee Absenteeism, Cure ardiness, and Bui1d Emp1oyee Mora1e (Chicago: The Dartness Corpora- ion, 1973),p 215 March is the month when absenteeism among Davison teachers is 4.9 percent, or at its highest rate. February is the month of second highest absenteeism at 4.7 percent per staff member. The fact that these two months are the months of highest absenteeism isn't too sur- prising because the nights are 1ong, the temperature is co1d, and there tends to be a higher rate of i11ness among students at this time of year. Another reason for a higher rate of absence at this time of year cou1d be that there is a re1ative1y 1ong period of time between the first of January and Easter with no schedu1ed vacations. The researcher was somewhat surprised to discover that May was the month of the year with the fourth highest mean absence rate at 4.6 percent. It wou1d appear that many Davison teachers wait unti1 May to “take“ accumu1ated 1eave time in order to use it before the conc1usion of the schoo1 year. Davison teacher absenteeism is at 2.1 percent in September, the 1owest rate of any month during the schoo1 year. This may be because most staff members are we11 rested and ready to get back to work. The financia1 cost of substitute teachers in the Davison district Mas $77,246.18 during the 1980-81 schoo1 year, or $214.57 per teacher. Teacher absences in the Davison Schoo1s cause financia1 out1ays of 535.00 per day per substitute teacher and increased staff time spent in ecuring rep1acements for absent teachers. The mean sa1ary for Davison eachers during 181-82 is $136.00 per day p1us $6.80 per day in retire- ent p1us $10.43 per day in other fringe benefits paid by the schoo1 istrict. In essence, the district is receiving very 1itt1e in return or this expenditure of $153.23 per day for each absent teacher. Teacher )sence is definite1y a financia1 burden on a schoo1 district's budget. 216 The instructiona1 costs of teacher absenteeism are immeasurab1e. ’ew substitute teachers, no matter how qua1ified, can do the job educationa11y that can be done by the regu1ar c1assroom teacher. Substitute teachers, especia11y at the secondary 1eve1 where extreme specia1ization of know1edge is often required, are often educationa11y ineffective. Unfortunate1y, substitute teachers are sometimes se1ected because of their avai1abi1ity rather than for their competence as instructors. The most critica1 cost of teacher absenteeism with which an administrator must concern himse1f is the cost in student 1earning Nhen the regu1ar teacher is absent. Severa1 of the fo11owing items of information discovered during the course of this study, whi1e not a1ways statistica11y significant, were nevertheIess of great interest to the researcher. Some of these items were: 1. The fact that ma1e staff members who resided within the Davison Schoo1 District were absent more often than ma1e staff members who resided outside of the district, yet fema1e staff members who resided outside of the district were absent significant1y more often than were fema1e staff members who 1ived inside of the district. 2. The fact that fema1e staff members were absent over twice as often for bereavement 1eave as ma1e staff members. 3. The fact that teacher absence rates were 1ower on ”payday Fridays” than on ”non—payday Fridays”. 217 4. That bui1ding principa1s perceive that teachers with better c1assroom management techniques are absent 1ess often than other teachers. 5. The fact that a re1ative1y few individua1s are using the greatest amount of time for absence. One major 1imitation of this study was the restricted range of popu1ation that was studied. That is, this study was 1imited to those Davison teaching staff personne1 who worked for a11 six years that were studied and were not absent during any of those six years for either 1ong-term i11ness (over two consecutive work weeks) or maternity-re1ated absence. These 1imitations took N from the 357 subjects who worked as teachers in the Davison Schoo1 District during the six years studied to 96 subjects who met the above criteria. Even though this study was 1imited to one schoo1 district which is a suburb of the City of F1int, the resu1ts may prove to be of inter- ESt to other administrators or board members of districts of 1ike size pr 1ocated in the same genera1 geographic area. Imp1ications for Future Research 1. A further study is needed to determine the corre1ations between student and teacher absence rates. 2. Further research is needed on the environmenta1 conditions, both physica1 and psycho1ogica1, that exist in schoo1s which might contribute to teacher absence. 218 3. Rep1ication of this study cou1d be done on a schoo1 district 5. of a simi1ar size in the Upper Peninsu1a, such as Escanaba, to determine whether patterns of teacher absence wou1d be simi1ar to the information discovered in Davison. . Rep1ication of the study with the exception of first offering a financia1 incentive to teachers not to be absent. One such incentive cou1d be an offer on the part of the board of educa- tion to divide equa11y among the teaching staff any monies 1eft in the account for payment of substitute teachers at the end of the schoo1 year. This study cou1d be repeated ten years in the future to com- pare simi1arities and differences with this study. BBBBBBBBBBBB BIBLIOGRAPHY :ademy for Educationa1 Deve1opment, Pub1ic Po1icy Division. Report on Teacher Absenteeism in the Pub1ic Schoo1s of 111inois to the Board of Education. I11inois Office of Education, Ju1y, 1977. imber, Chrissie. ”Student and Teacher Absenteeism.“ Phi De1ta Kappa Fastbacks, No. 126, 7-45. ‘idges, Edwin M. and Ha11inan, Maureen T. “Subunit Size, Work System Interdependence, and Emp1oyee Absenteeism.” Educationa1 Administra- tion Quarter1y, XIV, No. 2 (Spring, 1978), 24-42. .pitan, James and others. Teacher Absenteeism. A Study of the Ohio Association of Personne1 Administrators, 6493 Tang1ewood Lane, Seven Hi11s, Ohio 44131. ucationa1 Research Service. EmpJOyee Absenteeism: A Summary of Research. Educationa1 Research Service, Inc., 1800 North Kent Street, Ar1ington, Va. 22209. 1iott, Peggy G. “Where Are the Students and Teachers? Student and Teacher Absenteeism in Secondary Schoo1s." Viewpoints in Teaching and Learning, LV, No. 2 (Spring, 1979), 18-19. 1iott, Peggy G. and Man10ve, Dona1d C. ”Cost of Skyrocketing Teacher Absenteeism.“ Phi De1ta Kappan, LIX (December, 1977), 269-271. Igore, T. J. ”Lega1 Embarrassment: Paid Sick Leave for Pregnant Teachers.” Phi De1ta Kappan, LIX (Apri1, 1978), 558-559. ine, Robert M. Conditions of Learning, 3rd ed. New York, N.Y.: Ho1t, Rinehart and Winston, 1977. d1er, Pau1 H. “How One Schoo1 System Cut Its Teacher Absenteeism in Ha1f.” American Schoo1 Board Journa1, CLXIV, No. 10 (October, 1977), 32. son, R. O1iver and Lafornara, Pau1. Co11ective Legitimacy and Organizationa1 Attachments: A Longitudina1 Case Study of Schoo1 Personne1 Absences. Paper presented at American Educationa1 Research Association annua1 meeting, Chicago, I11inois (Apri1, 3-7, 1972). 219 220 Har1an, Vivian K. and others. ”Is Teaching Hazardous to Your Hea1th?“ ingtgnztor, XXCVI, No. 1 (August/September, 1976), 55—58, Harmischfeger, Annegret and Wi1ey, David E. ”Schoo1ing Cutbacks and Achievement Dec1ines: Can We Afford Them?” Administrator's Notebook, XXIV (1975). Keavney, G. and Sinc1air, K. E. ”Teacher Concerns and Teacher Anxiety: A Neg1ected Topic of C1assroom Research.” Education Research. XLIIX (Spring, 1978), 273-290. Landsman, L. ”Is Teaching Hazardous to Your Hea1th?” Today's Education, LXVII (Apri1/May, 1978), 48-50. Lansom, Joseph W. How to Reduce Emp10yee Absenteeism, Cure Tardiness, and Bui1d Emp1oyee Mora1e. Chicago: The Dartness Corporation, 1973. _idd1e, James. Reduction of Teacher Absences. Birmingham Pub1ic Schoo1s, Michigan (December, 1974); Monograph. 4an1ove, Dona1d C. and E11iott, Peggy. ”Absent Teachers . . . Another Handicap for Students?” The Practitioner, V, No. 4 (May, 1979). Reston, Va.: Nationa1 Association of Secondary Schoo1 Principa1s. 1azer, Irene R. and Griffin, Marjorie. Perceived and Experienced Stress of Teachers in a Medium Sized Loca1 Schoo1 District. Tacoma, Wa.: Office of Hea1th Education, Tacoma Pub1ic Schoo1s. Iew York State Education Department, Division of Research. Teacher Attendance Patterns. Technica1 Report No. 7 of a Study of Schoo1 Ca1endars. A1bany, N. Y.: New York State Education Department, 1978. ew York State Office of Education, Office of Performance Review. Teacher Absenteeism in New York City and the Cost Effectiveness of Substitute Teachers. A1bany, N. Y.: New York State Education Department, January, 1974. 1son, Martin H. ”Identifying Qua1ity in Schoo1 C1assrooms: Some prob1ems and Some Answers.” Centra1 Ideas, XXI (February, 1971), 11. ickhardt, C. E. ”Fear in the Schoo1s: How Students Make Teachers Afraid." Education Leadership, XXXVI (November, 1978), 107-112. 155811, R. D. ”Prob1em Drinking in the Education Profession.” Phi De1ta Kappan, LX (March, 1979), 506—509. 221 usse11, R. D. Teacher Absenteeism and Re1ated Po1icies for Supp1e- menta1 Remuneration. Suburban Schoo1 Study Counci1, Pa.; South Pennsy1vania Schoo1 Study Counci1; Pennsy1vania University. Graduate Schoo1 of Education, Pennsy1vania, 1970. Teacher Absenteeism, Professiona1 Staff Abuse Report. Produced and researched by the Pennsy1vania Schoo1 Boards Associa- tion, Harrisburg, Pa., October, 1978. Teacher Attendance Improvement. A Joint Business—Teacher Project. Newark, N. J.: Greater Newark Chamber of Commerce, August, 1975. ________. "Teacher Burnout: How to Cope When Your Wor1d Goes B1ack.” Education Digest, XLIV (March, 1977), 7-10. immering, S. and McCreery,-M. “A1coho1ic Teacher: A Growing Concern of the Next Decade." Journa1 of Drug Education, VIII, No. 3 (1978), 253-260. APPENDICES APPENDIX A A FINAL LOOK AT THE THEORY APPENDIX A A FINAL LOOK AT THE THEORY In this study, the researcher made an effort to use the genera1 incip1es of ”Invo1vement Management" as taught by Dr. Christopher )wer of the Department of SocioTogy of Michigan State University. Dr. Sower has expressed the concept that the community and impetent information are both power forces. The "community good” is superior power force to individua1 desires or actions. When excessive sence on the part of a teacher or teachers is harmfu1 to students' ucation, it is harmfu1 to the entire community. Dr. Sower has indicated that the stages of the invo1vement process which an action moves through one or more units of socia1 organiza- n can be summarized as fo11ows: Convergence of interest on the part of one or more individua1s who then make the persona1 decision to risk initiating the action into the units of organization which are re1evant to what they want to achieve. The initiation stage begins when they first imp1ement their decision to go into action. The 1egitimation and sponsorship stage consists of a dua1 process. One is a search for 1egitimacy within the norms and goa1s of the organizationa1 units. The initiators use appea1s and justification to persuade the peop1e to move from indiffer- ence into support. The other process is to use various avai1- ab1e channe1s of communication to gain access to those units of the tota1 organization which are re1evant to the goa1s of the action. The goa1 is to move those who are either neutra1 or 222 223 opposed into either sponsorship or approva1. The opposition has to be contained if the action process is to continue. Often some of the goa1s have to be changed in order to gain 1egitimacy and support from the rest of the organization. This is ca11ed justification of the charter (group goa1). In summary, these princip1es have come to be ca11ed normative sponsorship; that is, sponsorship by the decision makers of an organization with its norms and goa1s. Dr. Sower made some further written comments on this dissertation Apri1 6, 1982. Those written comments were: ORGANIZATIONAL DECISION MAKING IN COMMUNITY SETTINGS 1. The community good is a superior power force to the rights and priviIeges of any member of the community (person or organi- zationa1 unit). 2. In issues about which there is controversy and a history of conf1ict, the definition of the community good usua11y a1so is controversy. (Schoo1 administration versus teachers.) 3. Competent information is an important power force in defining the community good, especia11y when the definition is in controversy. 4. The proposition in the Robert Amb1e thesis is that the schoo1 superintendent's ro1e (usua11y one of the ro1es in conf1ict) cou1d represent the community good if it compi1ed competent information about teacher use of sick 1eave—-especia11y in those cases which are more for persona1 benefit than for the community good. 5. Then, if this information is presented to the re1evant units of the schoo1 system without vio1ating the ’ru1es of initia- tion,‘ it is predicted that the corresponding ro1es wi11 be ob1igated to respond: a. At 1east not in pub1ic opposition b. With some neutra1ity, but possib1y with some sponsorship. This has been achieved. 1Increasing the Effectiveness of_Agricu1tura1 Deve19pment Opganiza— s, a working paper by Dr. Christopher Sower, Department of Socio1ogy, igan State University, February 5, 1982, p. 4-5. 224 6. But, now some specific sponsorab1e innovations are needed. Preferany, these shou1d be deve1oped by some joint body, consisting of teachers, the teachers association, the board of education, an administrator (but not the superintendent), and members of the community. Keep the superintendent's roIe above the immediate fray. He can co11ect information for each future year. Thus, this may be a predictive mode1 for achieving change in teacher use of sick 1eave. 8. Can any specific ru1es or practices be changed? for each person taking sick 1eave to report persona11y to an individua1--by phone? Maybe 1ater in the day if not at 6:00 a.m. Have a recorded message of the conversation. 9. The variab1e of TIME. Thus, can a process of sett1ing other schoo1 issues be defined? a. Co11ect competent information. b. Invo1ve a11 re1evant ro1es in the information co11ection process. Search for workab1e innovations--sponsorab1e ones, with c. community members a1ways invo1ved in the process. d. Fo11ow the 'ru1es of initiation' in the changes. The researcher p1ans to fo11ow Dr. Sower's suggestions for the e1opment of a joint body during the fa11 of 1982 in an attempt to ive at some sponsorab1e innovations concerning the most productive of teacher 1eave time. Dr. Sower's comment number ten may be best imp1emented through a t effort of Michigan State University, Mott Community C011ege and Davison Community Schoo1s Community Education Program. The co11ec— expertise of these three organizations cou1d be uti1ized to offer urse or program that wou1d present an opportunity for sett1ing other 01 or community issues. University credit, community co11ege it, or simp1y an opportunity to participate in the so1ution of schoo1 Is it possib1e community prob1ems cou1d be offered, depending upon the educationa1 tus of the participants. The opportunity for studying and so1ving munity issues wou1d be un1imited if this process proved to be cessfu1. APPENDIX B STATISTICAL INFORMATION 1974-75 THROUGH 1978’79 226 nb.hva.a av.mnm NM.Nmo.a om.mmm oo.ama N¢.HNM oo.Hm oo.ov oo.Hn ww.~n hw.Nh av.aw anuov nh.mo~.m om.om nN.HVH~H mm.mmn wo.mmm Nm.mhm co.mw ooovw hm.ooa om.ww. mh.NNH 00.5mm mau09 mm.mwn om.mm mH.mon om.whm nn.Nn mn.vm oo.HH om.Ha om.m nm.m om.mN oo.h~ I mhiah mm.hh~ om.ma nn.mmN nn.m0H om.m~ om.u~a om.~m oo.HH om.mN om.va oo.~n oo.Hn ohnmb mm.mHN i ww.n~ om.mm~ I om.wHH om.mm om.om om.HH oo.HH om.H cc.m om.oa oo.hH chirp mm.HmN oo.HH. mm.om~ i om.hm nn.ov m~.NMH on.NH om.NH co.o~ oo.mm mN.bN on.vn whips mb.mo~ mh.bN oo.mba om.mw oo.w~ om.nw ' ooJHH om.oa om.h om.m om.NH om.mH hhwwh mm.ee4 me.emm 044909 .9m4e ee.em em.mm .04 .em mm.me mm.mmm 44909 mmiu ee.em mm.emm ammm .um ee.em mm.em 494m .99 .ee.mm me.em 44909 .44 ee.e em.mm uuoumo: em.m em.e nonaos9 ee.e em.mm ommmm mm.e ee.m mmmm ee.e 44.44 mauve na.u mm.vm Hauucou wWNZHmDm AOOmUw nu.hNN oo.ma nu.NHN om.hw mH.vm NH.HAH oo.NH oo.uH no.0" om.HH omnma om.vn whlmh mm.NvN qufioa .PMHO ee.em .04 .mm ee.mmm 44909 mmuu mmmmmu nvmm .um em.em 404m .99 om.hHH A4909 .HM I ee.mm uuoumoz 0e.m4 4045049 em.em omamm em.vm 444m ee.em 00940 em.vm muuucou ! .IIIMbHHh 227 mm.m- I mn.mm mm.HHN ‘ om.vm mv.Hn ha.mw om.Hm om.m om.N on.oa oo.m~ hH.uN Hnuoa Hm.hmv l mH.oN mu.hmv mw.HHH «H.5w mn.mnN cm.Nn "noun oo.mn on.a~ oc.ov oo.ow Huuoe mw.~m oo.n om.m¢ ww.ma co.H oo.m~ om.a om.H oo.a oo.mH oo.oa which nn.mm oo.m nn.wb nn.m~ oo.om oo.on co." om.n oo.H oo.HH oo.m om.HH munch em.me ee.m em.ee mm.mm mm.94 em.9v ee.m ee.e ee.e ee.e em.e ee.em whlhh me.mv “mums: mm... mqumu me.9m 94.4 mmqmuu ee.m 94.4 eeuem nm.wh om.m mm.Nh nm.MH om.w om.om om.oa om.o om.m oo.H om.NH om.0H hhtwh me.0m me.em oe.m mm.m Hm.mv om.mn «a.mm 9w.o~ no.m mm. oo.aN oo.om 0m.m ee.m. I oo.w om.~ oo.m ee.mm . 1 oo.m oo.m whims whim“ K000 oo.oam av.om 00.m ee.m 00.404 no.e9 mm.em me.9m «a.mm 0m.vm ne.mm .0m.ev ee.e ee.mm ne.o 0m.0m em.e ee.mm om.v 00.4 00.mm 00.~ 00.em 00.0 whims. mnunn 3ng >300 m44909 .9490 .04 .mm 44909 9414 4944 .9m 4944 .99 44909 .44 900040: confiony ommmm Adam moudo mununou 444909 .930 .04 .mm 44909 44.4 4044 .um 4944 .99 44909 .49 9000403 someony ommmm dawn nouow manage” 228 00.va 00.va 00.m 00.0 Hnuoa 00.0w 00.0m 00.A 00.Hm 00.0H 00.hH Hauoa 00.0m 00.0n 00.0 00.6 00.v 00.NN Huuoa 0m.m 0m.m 0m. 00.m 00000 00.0 00.0 00.H oowu 00.n mhlmh 00.0H WQGHOB .HmHQ 00.vH 00.m 00.0 llleukb HMdBHAH Hmbb .04 .04 A4909 NHUM 4044 .um consona qufiofi .BWHG .04 .04 AdBOH NH!“ consona 4490400 4044 .44 4044 .40 mddaoa .HmHo .04 .04 A4909 «HIM 4003059 4044 .90 00000 muuucou 229 mv.0h n mom + vm.mm0.mm 2.0.0 0m.mme.nm. mme. 3|. eme. ee.mm eme. ee.em mum. ee.emm 4mm. mm.mme nee. m9.eem.m mme. m9.0e«.m mem.m ee.emm.0 mmmmumm «Mum 0N.HHm.H 0N.HHM.H 0«.Hdn.d 0N.HHM.H 0N.HHn.a 0N.HHM.H 0N.HHn.H 0N.HHn.H 8.42.4 09030009 99.3432 .4.m.o 9909. x000 ucaau>uouom anonflnlm Hooaum 40904900 0%fln MOdm E .0: 3 at A: AC 3 SO 43 SO 43 9.0.04 0083 and?" nNfioN «mica 40.02 mm§mm 00.93 00.004 3&04 a: 00.404 on.n.—flm “0.000 snéNnA 00.0.43 «n63..— n~.0no mafia“: 00.5.3 50.0.3 .28“. 155' III" II." me.4m 04.004 04.44m 00.0em .0m.mmm 00.44m 04.044 em.mem me.mem 04.044 mm-eme4 40.04 40.4mm mm.ee4 00.4mm 04.0em em.mem en.m4m em.m0m 00.nmm 40.044 em-4404 me.mm4 em.mnm em.4mm mm.40m 04.40m 44.404 “4.004 90.mem 40.044 mm.4m mm-e404 em.e0 me.nem ee.mem 4e.nmm 40.00m 44.99m 40.40m 44.0mm mm.m44 00.04 04-4404 44.09 m4.mem mm.004 44.0mm m4.4em 00.404 00.04m 00.4em mm.nem m0.em4 04-440. acne Nun. 4mu« .4.: 40mm .040 .uoe anmm ammm ammuw mmmwmmmwmm-mmmmmm 4ee 400 440 440 440 Ame 00.4 94.404 04.004 90.40m 40.444 me.e00 444: 00.44 mm.em0.4 0m.eee.4 me.m4e.4 me.mme.m e4.mme.m 44909 .-u1 mmammm «4.044 00.0em qummw mmamwm mm-eme4 - 00.440 44.004 44.009 mm.mme m0.mee e4-9404 mw - 00.04m 44.004 ee.eem 00.90m 40.404 mm-eme4 02 00.44 e0.0mm mm.0em m0.4nm 40.040 nm.mem 04-9404 00.4 00.04m me.mmm m4.nem em.m04 44.400 04-0904 Nummmmmm 44044” Numumumm 4umuummum Numuumm 4ummmm .-|------ an NE 00 mr<0 en.m no.0 4444 00.94 em.mm 44909 m0.m 00.m 44-0904 04.4 04.0 04-4904 04.4 00.e mm-eme4 nn.m 04.4 49-9904 40.4 00.0 04-0904 0049-4404 0049-0444 .N uvcnm 43.11 in. a- A: 48 43 30 AC AC 30 44.40 3.40 . 44.4 04.04 44.04 44.0 44.0 40.0 04.0 44.0 44.0 240.: w 44.04 00.04 00.44 40.40 44.40 40.44 40.00 44.44 44.44 44.8.4 h .4414! 3 04.44 00.0 40.0 00.44 44.0 40.4 00.0 44-4404 ... 44.0 00.4 04.44 40.0 04.0 40.4 04.44 00.4 00.44 04-4404 4. 04.4 04.0 40.04 00.0 00.0 04.0 04.0 40.44 04.4 44-4404 4.. 40.4 00.0 40.4 04.0 44.0 04.0 00.0 44.44 04.04 07442 H. 40.0 04.04 04.0 40.44 00.0 44.0 40.4 00.0 44.4 070404 4.. .lE'dloum 42400 440.0 4mm 4444 mm #4 fl m .... 49440..— uvuhu Nu .. 04.04 00.4 44.0 04.4 44.4 .4444: 44.44 40.04 00.40 44.04 44.44 44.80 44.44 00.4 44.0 40.4 .4444! 44-4404 04.0 00.44 04.04 40.0 44.0 04-4404 04.4 04.4 40.0 44.4 44.4 441.404 44.4 40.4 04.44 40.0 44.4 074404 N 04.44 44.0 40.4 44.0 40.0 040404 2 ...... 4% a a ..2 «am 44.0 44.0 5.40 44.0 04.4 5.0: 44.44 44.04 4490.4 00.44 04.44 4.4.8.4 0|4.l0 a 44-4404 04.0 40.0 444404 44. 4 00.4 04-4404 04.0 04 .4 04-4404 44.0 44.4 44-0404 40.4 44.4 44-4404 00.0 40.4 04-4404 40.0 00.4 04-4404 00.0 00.4 040404 44.0 04.0 04-0404 a all. |.|ll' .4 ..4 Ln 0 uuwwxuvng 434“qu 232 aw.a~mm I cm.n~m a~.w0vm w~.av@~ mw.mow~ hm.av~m mh.ham ma.mmv am.mwa vm.m=m am.~am ~m.w~mu m an Mucupr E1 eN.H~nA "l oo.~h o~.ovN« an.vmv ec.w- om.aom no.5w mh.Nu mh.nm mn.hw om.VNH m~.cm~ .mu:0$ bv.ona~ o.am~ o~.vqu m.w~ NM.~NQH m.~v~ n=.v~m a.mm mn.hmn e.an ou.o~o~ m.mc~ cm.mo~ a.mu ne.no~ c.n~ om.ha~ o.m~ na.mm m.ma om.hm~ e.vm oo.aa~ c.9N mNan .04505 ahlmhan 00.0404 04.004 00.4404 4.404 mmqmm-I 00.44 40.404 0.44 40.0404 04.444 04.4404 0.044 04.000 04.40 mmqmmul 0.00 40.444 00.44 00.444 0.04 44.040 00.404 40.4404 0.444 44.404 mmqmw- mmqmwlu 0.44 00.40 44.44 44.404 0.44 40.444 04.04 40.404 0.04 00.44 44.44 00.40 0.44 00.004 00.44 00.444 0.44 44.004 04.04 00.044 0.04 mummII-qmmmwm mammlllqmmmmw 04-4404 44-0404 III-II-IIIIIII-I-IIIIII >=<223m m>lm Nm.nmcm m.~h~ I. cm.a~u o.v~ Na.hha~ m.omN mh.amn o.~a ww.onn o.av Hv.NOAH m.a- I! cm.vw °.v~ co.nh o.m~ om.hma o.c~ mm.c>d m.m~ mm.~m~ c.w~ om.mmm a.mm mNan .mn:09 whlmhmu m4z<223m zumucmsw4m 4A<20mzmm I} A" 234 .uzoh\.v>< co.v~ oo.am oo.am mm.wmm mH.th mama m4muOH o~.HHMH ON.HHMH ON.HHMH om.HHMH ow.~HMH .m4zoh oo.cH wo.~m mm.mm ahlmhad - - - 00.44 00444040 "4004444: 04.44 00.0 00.0 00.4 40444042 ".<.0.0 00.4 00.44 00.44 - 00444040 .4000 4000 00.04 40.44 40.04 40.04 40440040 “0000 04.40 44.04 00.044 04.00 00444040 uezmzm><0000 04-4404 44-0404 04-0404 04-4404 "4000:440000 mw<0 zm=ao I >K<223m mIm IES 0n I "firgwgmflmgmwglg