‘— ‘— \ "4 ‘ .. socIo - ECONOMIC, PHYSICAL HOUSING, LOCATION; ~ AND SOCIAL PSYCHOLOGICAL MEASURES. ,USED'AS . - ' j PREDICTORS'OF HOUSING SATISFACTION. Thesis for the Degree of M. A; . MICHIGAN STATE UNIVERSITY TRACEY ANNE FEILD -1975". (J “ ABSTRACT SOCIO-ECONOMIC, PHYSICAL HOUSING, LOCATION, AND SOCIAL-PSYCHOLOGICAL MEASURES USED AS PREDICTORS OF HOUSING SATISFACTION By Tracey Anne Feild The purpose of this study was to examine the relative importance of four groups of variables, socio-economic, physical housing, location, and social—psychological, as predictors of hous- ing satisfaction. Social-psychological variables were included as measures of general feelings, attitudes, and beliefs about life and specifically interpersonal relationships. This attempted to explore the notion that one's contentment and satisfaction with life and the interpersonal relations one has affects contentment or satis- faction with the house. The data used came from a larger interdisciplinary field study entitled, "Functioning of the Family Ecosystem in a World of Changing Energy Availability," funded by the Michigan Agricultural Experiment Station. Data on housing satisfaction, housing facil- ities, and family data were obtained using self-administered ques- tionnaires. Demographic data were obtained through personal interviews. Census data were also used. Tracey Anne Feild The hypotheses were tested using multiple regression analysis to determine the independent contribution of each of the four groups of variables individually; and the contribution, direc- tion of relationship, and relative importance of each variable with all variables in the equation. It was found that with all independent variables in the equation, 2l percent of the variance was explained (R2=.2l6). The most meaningful independent variables in predicting housing satis- faction in order of importance were: Value per room, bedroom defi- cit, family effectiveness, median education of the surrounding area, and percent of owner-occupied single-family dwelling units in the area. The findings indicate that as groups of variables, physical housing factors were most important as predictors of housing satis- faction. There appears to be room for further study in determining social-psychological and neighborhood measures predicting satis- faction. Socio-economic variables appear to have little predictive value for housing satisfaction. Though directions of relationships hypothesized were sup- ported, the level of meaningfulness of each of the variables and each group of variables varied substantially indicating some measures were not useful within each of the groups. Further research into the area of predictors of housing satisfaction is warranted. SOCIO-ECONOMIC, PHYSICAL HOUSING, LOCATION, AND SOCIAL-PSYCHOLOGICAL MEASURES USED AS PREDICTORS OF HOUSING SATISFACTION By Tracey Anne Feild A THESIS Submitted to Michigan State University in partial fulfillment of the requirements for the degree of MASTER OF ARTS Department of Human Environment and Design 1975 ACKNOWLEDGMENTS I would like to take this opportunity to express my thanks and appreciation to the following people for their contributions to my research experience: Dr. Bonnie Morrison, as my major advisor,for her sincere interest in my personal growth and development as well as in my research; and for her encouragement, help, and advice particularly throughout the writing stages of this thesis. Dr. Peter Gladhart, as my methodological advisor, for his statistical, methodological, and theoretical advice, his critical thinking, and high standards; and to the long hours of help he gave me throughout the summer in deciphering the computer. Dr. James Zuiches, as a committee member, for his support and genuine interest in the final stages of my research after sub- stituting for another committee member on leave. Dr. Mary Andrews for her statistical and computer help and her sincere interest in my research. Sandra Clarkson, Mary Ann Eichenberger, and Jan Hogan, fellow graduate students, for their confidence, understanding, support, and friendship throughout; and especially to Sandy Clarkson for so much extra moral support as well as typing and editorial help. ii Mrs. Nancy Axinn, a very good friend and colleague, for her concern, support, and encouragement throughout my graduate program. Marilyn and John Feild, my parents, for their continuing support of and patience with my educational route. Peter Paluch, a special friend, for always being available when I needed a shoulder to cry on. iii TABLE OF CONTENTS LIST OF TABLES LIST OF FIGURES . LIST OF APPENDICES . Chapter I. INTRODUCTION Problem Statement . . . Mobility and Satisfaction . . Barriers to Mobility and Satisfaction . Modes of Adjustment to Housing Theoretical Framework Discursive Definitions Dependent Variable Independent Variables Assumptions Hypotheses II. REVIEW OF THE LITERATURE Housing Satisfactions and Dissatisfactions . Perceptions of Self and Effect on Outlook III. METHODOLOGY . Collection of the Data The Sampled Community . . Description of the Sample Operational Definitions Dependent Variable Independent Variables . . . Other Variables Considered for Usage Statistical Analysis . . . IV. FINDINGS AND DISCUSSION . Findings Discussion iv Page vi vii viii Chapter Findings Discussion Findings Discussion Findings Discussion Findings Discussion Conclusions V. CONCLUSIONS, LIMITATIONS, AND IMPLICATIONS Conclusions Limitations . . . . . . . . ,. . . . Implications and Suggestions for Future Research . APPENDICES BIBLIOGRAPHY . Table SDCDNO‘U'l-FDMN _.a _.| ._a N —" o C C . l3. I4. 15. 16. 17. LIST OF TABLES Array of Specifications of Importance to the Families as They Looked for Their New Homes Urban-Rural Breakdown of Sample Tenure Status of Sample Structure Type of Sampled Households . Dwelling Type of Sampled Households Family Type Age of Wife Family Income Educational Attainment of the Wife Occupational Status of Husbands and Wives Descriptive Statistics on Satisfaction Scale Regression Results for Socio-Economic Variables with Housing Satisfaction Regression Results for Physical Housing Variables with Housing Satisfaction . . . . . Regression Results for Location Variables with Housing Satisfaction Regression Results for Social-Psychological Vari- ables with Housing Satisfaction . . . Regression Coefficients, Standard Errors, F-Ratios, Probability of Sampling Error, and Multiple Corre- lations of Independent Variables on Satisfaction with Housing . . . . . . . . . . . . Rank Ordering of Independent Variables by Size of Standardized Regression Coefficient and F-Ratio with Satisfaction with Housing . . . . vi Page 22 35 36 36 37 37 38 38 39 39 41 5] 51 52 52 54 6O LIST OF FIGURES Figure Page 1. Model . . . . . . . . . . . . . . . . 12 2. Model for Viewing the Decision to Move . . . . . 25 vii LIST OF APPENDICES Appendix Page A. Selected Questionnaires . . . . . . . . . . 74 B. Reliability Coefficients of Social—Psychological Scales . . . . . . . . . . . . . . Bl C. Criteria for Neighborhood Groupings . . . . . . 83 D. Correlation Coefficients of Variables . . . . . 85 ~viii CHAPTER I INTRODUCTION Human beings function as part of various and complex struc- tures or systems. One of the basic social organizations is the family. Most everyone is born into, grows up within, and eventually begins one's own family. In addition to a social structure, Ameri- cans are very much a part of a spatial structure. They function within their social unit in a particular place in space. For the family this "place" in its most basic form is the house. Identifi- cation with a place, a house, a neighborhood, a city or state is often as important as identification with a social structure such as a family, a country club, a religious, or an income group. The two types of structures, social and spatial, cannot always be dis- tinguished,the discrete values of each are often vague. One's place in the social structure may determine one's place spatially and vice versa. A change of place in one structure may cause or be caused by a change in the other. Some researchers recently have attempted to look at the interactions between social systems and spatial sys- tems. The emphasis on the relationships between these two types of systems has surfaced within the last ten years in modern urban America under the label of man-environment studies with emphasis on the quality of life. Although the concept of quality of life seems l broad and poorly defined, various dimensions that make up the con- cept have been studied. One of the most important dimensions studied is housing. In what type of house does the family live? Does the house meet the family's needs both physically and psychologically? In what kind of neighborhood is the house located? Does the neigh- borhood meet the family's needs? Would they prefer to be housed elsewhere? Or are they satisfied there? The answers to these ques- tions may well determine any one family's satisfaction with their housing, and thus reveal one dimension of their quality of life. Problem Statement This study examined the concept of housing satisfaction and its relationship to four groups of measures: socio-economic, physical housing, neighborhood or location and social-psychological factors. Socio-economic factors and physical housing factors have long been used by researchers as important factors in determining housing satisfaction. Neighborhood or location factors have been considered important but perhaps not as important as physical hous- ing and socio-economic factors except when related to status increases due to changes in socio-economic characteristics. Social— psychological factors as defined in this study related to housing satisfaction have not been examined until this research and are hypothesized to be at least equally important to housing satisfac- tion as the other three factors. The first three groups of factors are based on an objective reality. How much income does the family have? How many children does the family have? Are they expecting more children? How many bedrooms does the house have? How well does the family's socio—economic status fit in with that of the neighborhood? However, social-psychological factors are based on the subjective reality of perceptions, attitudes and feelings more attuned to the idea of housing satisfaction. Housing satisfaction as measured here doesn't deal with specific properties about the house itself, but to feelings about the house. Foote, et al. con- firmed this belief: Dissatisfaction with housing contains a subjective element. There is some uniformity between level of satisfaction and objective characteristics of the dwelling, its cost and its surrounding environment and location. But correlation is not complete, since satisfaction is always partly a sub- jective phenomenon, varying from family to family, and depending upon the different standards by which they judge, as well as the different goals which they look forward to achieving (1960, p. 157). Thus, standards and goals of housing satisfaction are surely related to their specific feelings, attitudes, and beliefs. A combination of these four groups of factors,therefore, should play an important role in determining housing satisfaction. Mobility_and Satisfaction The idea of satisfaction with one's house is itself composed of a number of dimensions. Many researchers in the area have related satisfaction to mobility. "The Consumer Votes by Moving" (Abu- Lughod and Foley, 1966) is a popular notion based on the belief that when a family becomes dissatisfied with its home, it can move to another. Gladhart, in a study of family mobility, viewed the deci- sion to move in this manner: In my view, the elements involved in a voluntary mobility decision include: (1) a family whose composition has changed, (2) a house which has not changed, (3) a norma-* tive context which defines the match between the house and the family as undesirable (l973, p. 7). Physical housing factors related to changing family needs play an important role in housing satisfaction. Changing family needs are related to changes in the family life cycle, changes in family size and changes in socio-economic life style characteristics. Changing family need also is related to family perceptions of housing need. A rise in socio-economic status may be followed by a move to a "better" home or a home more suited to increased status. Leslie and Richardson synthesized this combination of factors: The verbalization of specific complaints about the present dwelling and the anticipation of more satisfactory features in a new dwelling may be the vehicle for the translation of life cycle and career pattern variables into individual decisions to move (l96l, p. 90l). A socio-economic status increase is related directly to spatial location. The desired change of housing can be unrelated to the quality of the house itself, but instead, to the neighborhood in which the house is located. Alvin Schorr stated: The physical move is a social move, an evidence of aspira- tion and a functional step in improving one's social or econ- omic situation (1963, p. ll). Historically in the American city, the status move has been outward from the city center to the suburban ring, at the cost of job acces— sibility. The private automobile, however, virtually has eliminated accessibility as a problem for middle America. Neighborhood factors are weighed with physical housing fac- tors and socio-economic factors in determining housing satisfaction. Not only must the physical and social structure of the family fit the physiéal space to attain a degree of housing satisfaction, but the social structure of the family must fit the social system or climate of the neighborhood environment surrounding the house. Both criteria must be met to arrive at an acceptable satisfaction level. If the social structure of the neighborhood does not meet the minimum expected or desired by the family, the fit does not exist and the family moves. Morris and Winter enlarged this point: The location of the dwelling unit and the nature of the area are prime determinants of the family's satisfaction with the dwelling and of its ability to accomplish other nonhousing goals. The quality of the children's educa- tion, for example, is greatly determined by the location of the dwelling (l975, p. 83). Physical housing factors, socio-economic factors, and neighborhood or location factors traditionally have been examined to determine satisfaction with housing as manifested through voluntary residential mobility. Sabagh, Van Arsdol, and Butler (l969) in a discussion of determinants of residential mobility concluded that metropolitan residence changes are composed of four dimensions: (l) family life cycle, (2) social mobility, both intergenerational and career, (3) residential environment including changing characteristics of resi- dence and neighborhood, and (4) social and locality participation which includes neighborliness and satisfaction with the nature and extent of participation. Barriers to Mobility and Satisfaction Voluntary residential mobility is based on the assumption that other housing is available at similar cost or that increased income offsets increased cost. For the low-income family, this may not be so. Sylvia Lane summed up the problem of the low-income family: Consider the Negro family with a shelter-paying ability below the entry point for the cheapest suppliers. The family finds shelter by violating the housing laws in many ways or it moves outside normal market channels. Movement outside normal market channels forces it to accept poor quality housing, to use the housing more intensely, and to remain underhoused . . . . The housing they occupy . . . is not what they would buy if they had a free market choice (l974). A family who has no choice in its housing due to economic restric- tions may be far less satisfied than one who has choices via economic flexibility. Beyond purely economic barriers, racial and ethnic discrim- ination confines housing opportunities to small, spatially well- defined and often overcrowded areas especially for those minority families who happen to be low-income. Another important barrier to mobility is referred to by geographers as "distance decay." This means that the probability of a family having knowledge or informa- tion about available housing and their preferences for that housing usually declines regularly with distance from the family's present location. Brown, Horton, and Wittick elaborated: The prime constraint on a migrant household's search pattern is provided by its awareness space, which may be defined as that set of locations within the urban area about which the migrant possesses some knowledge (l970, p. l76). The awareness space is derived from the household's activity space, or locations with which the household has direct contact through various activities, and its indirect contact space, or locations about which the household has some knowledge through indirect con- tacts such as friends, relatives, or mass media. However, Brown et al. indicated that the searching for alternative housing units takes place within the household's search space: The search space is contained within its awareness space and comprises those locations within the urban area which the migrant household perceives as being likely to satisfy its aspirations with regard to a new residence. Thus, it is explicitly recognized that, on the basis of criteria relevant to the utility of a residential site (such as its accessibility to urban amenities or its social envir- onment), certain locations within the urban area will be eliminated from consideration before search begins (l970, p. 176). If the awareness space is small, the search space could be almost nonexistent, no move will be made, housing satisfaction remains low. The fact that housing alternatives do or may exist is meaningless if not perceived within the household's search space. Socio-economic 'Characteristics such as low-income, low educational attainment, or racial or ethnic discrimination tend to lessen the family's aware- ness as well as search space. Therefore, their housing satisfaction may be low, but this dissatisfaction would not be manifested in a move. For this reason voluntary mobility cannot be used as the only measure of housing satisfaction. Modes of Adjustment to Housing_ Morris and Winter (l975) viewed mobility as one facet of family housing adjustment. They suggested that if housing does not fit needs, a housing deficit exists. This deficit may be reduced by one or more of the following ways: (1) residential mobility, (2) residential adaptation, or (3) family adapation. Morris and Winter also suggested: Because of the presence of constraints, both intra- and extrafamilial, the family may be forced to compromise or relax their norms and utilize reasonable housing goals. Such compromises are achieved by the development of pref- erences for both means and goals that are relaxations of norms (l975, p. 79). Although the middle or upper income family may choose the first mode of adjustment, to move when the house no longer fits their needs, they also may choose the second mode of housing adjustment, residential adaptation. This would entail modification of the home in some way through redecoration or remodeling. The third mode of housing adjustment, family adaptation, will be examined in greater depth. What makes a family adjust their own standards or norms to confirm to the existing reality? A family without economic or information resources may have little choice but to adjust its norms. The house may not fit their needs in a variety of ways but without the resources to change or improve hous- ing, the only alternative available may be an adjustment in their own standards. However, why is it necessary for adjustment behav- ior to occur? It may be possible for the family not to adjust its norms, but instead, to live with a constant dissatisfaction. There may be certain psychological attributes or personality types that do not conform to family housing adjustment behavior. Theoretical Framework Uriel and Edna Foa (1973) suggested that human beings need access to material or economic resources as well as to particularistic resources. Particularistic resources are those that deal with one's interactions with other human beings (interaction, love, etc.). Access to interpersonal relations and the quality of these relation- ships, according to the Foas, strongly affects one's perceptions of, and needs for economic or material resources. The Foas theorized that unless a minimum need for particularistic resources is ful- filled no quantity of economic or material resources will satisfy the need. They suggested that in modern, urban America, people do not have access to a sufficient level of particularistic resources and, therefore, attempt to substitute material resources which are more readily available. This leads to emphasis on material goods and overconsumption. The problem lies in the fact that they are not equally substitutable. Their research indicated that, "(a) the substitute is demanded in greater amounts, and (b) this greater amount produces less satisfaction" (Foa and Foa, l973, p. 22). One might interpret this to mean that a person lacking in a particular- istic resource might attempt to substitute a better or bigger home (as one example) but still not be satisfied with that home since the need is interpersonal. This dissatisfaction, in this case, would not reflect the home as much as the availability of particu- laristic resources. If these resources involve interpersonal rela- tionships, one can look at several psychological concepts in an attempt to get a representation of how one views oneself in relation to others. The most basic of these concepts might be that of self- esteem. Although self-esteem is a feeling of self-worth, it can 10 only be measured by how one feels towards self in relation to others. It is generally agreed that a person's self-esteem is determined largely by what others think of him/her. This suggests that one without access to particularistic resources might have low self-esteem. Another social-psychological concept that could be used as a measure of accessibility to particularistic resources is that of social isolation, which refers to a feeling of isolation from group standards. This could be related highly to the residential mobility dimension identified by Sabagh, et al. (1969) as social and locality participation. Closely related to social isolation is the concept of anomia referring to the individual's generalized, pervasive sense of "self- to-others belongingness" as compared to "self-to-others distance or alienation" (Srole, 1956, p. 711). If one feels very alienated from those around him/her, it may be because one's access to particular- istic resources is limited. . A fourth social-psychological factor deals with an individu- al's belief in external control. According to Rotter, a person is said to be externally controlled: When a reinforcement is perceived by the subject as follow- ing some action of his own but not being entirely contingent upon his action, then, in our culture, it is typically per- ceived as a result of luck, chance, fate, as under the con- trol of powerful others, or as unpredictable because of the great complexity of the forces surrounding him (1966, p. 1). An externally controlled person may not believe that any adjustment one makes in life would make any facet of life happier or more ll satisfying. This individual probably would not behave in accordance with family housing adjustment theory, because adaptation or mobility would not be perceived as a means to increased housing satisfaction. Although this perhaps does not measure directly one's access to par- ticularistic resources, it instead may determine one's ability to use resources to achieve specified goals. The last social-psychological concept used here in relation to particularistic resources was family effectiveness which deals with the perception of the family unit by its members. How the family functions as a unit and how each of its members feels about that functioning can very much depend on the physical amenities, layout, and size of the house. A family with a house that doesn't fit its needs may pay through decreased family effectiveness. More importantly, however, the family may function poorly as a unit regardless of housing considerations, and this low effectiveness could be manifested in perceived dissatisfaction with housing. Family members who feel their family does not function well as a group may have fewer particularistic resources to turn to when needed, and thus feel unhappy and dissatisfied in general as well as with their home. These five concepts were used to give an insight into the family's social-psychological attitudes, beliefs, and perceptions regarding the Foas' particularistic resources. Perceptions of the quality and quantity of interpersonal relationships in relation to interpersonal need may well help determine one dimension of the family's quality of life, that is satisfaction with housing. 12 The theoretical approach advanced in this study suggests that housing satisfaction (H5) is a function of four major groups of variables. Thus for any family (i), at any point in time (t), for any particular dwelling unit (k): iHS where: SES PHY LOC PSY f (iSESt’ kPHYt’ kLOCt’ 1-PSYt) socio-economic variables physical housing variables location variables social-psychological variables Specifically these groups break down into individual variables and the model becomes: .HS 1 where: Figure l.--Mode1. VALU BD TEN f(1.INC ED t,k t,k , t’ i t’ k TYPE LOCt, MINCt, MED , OWN k ’ k k k t k t’ iEST 1.ISOLt, 1.ANO t’ t’ i family income education of wife value per room bedroom deficit tenure status structure type location median income of area median education of area percent owner-occupied, single family dwellings in neighborhood self-esteem social isolation anomia external control family effectiveness l3 Discursive Definitions Dependent Variable l. Satisfaction with housing: This was a fifteen-item Likert-type scale used as the major dependent variable. The scale was designed to determine the family's overall satisfaction with the housing unit. (See Appendix A, p. 75.) Independent Variables l. Socio-economic factors: Defined as family income and education of wife. Specifically these variables were: a. Family income: Total gross family income for 1973. b. Education of wife: Total number of years of formal education, including vocational and technical school, of the wife of the household. 2. Physical housing variables: Made up of four measures of physical housing quality. Specifically these variables were: a. Tenure status: Used as a dummy variable where owner-occupied status equaled one and renter-occupied status equaled zero. b. Structure type: Used as a dummy variable where single-family dwelling type equaled one and nonsingle family dwelling type equaled zero. c. Value per room: Designed as a measure of housing quality computed for owner-occupied units as the value of the house divided by the number of rooms. For renter- occupied units, it was computed as the yearly rent muliplied by 10 and divided by the number of rooms. 14 d. Bedroom deficit: Determined by using a measure of bedroom need computed by taking cultural norms of sharing of bedrooms dependent on ages and sex of children. The need was subtracted from the number of bedrooms the housing unit actually had to determine a plus or minus bedroom deficit. 3. Location factors: Made up of four measures designed to determine the overall quality of the neighborhood in relation to the individual sample households. Specifically they were: a. Location: Used as a dummy variable where urban equaled one and rural location equaled zero. Urban was defined as being located in the city of Lansing, East Lans- ing, or the surrounding suburbs, while rural was defined as being located in a township with no urbanized area. b. Median income: Defined as median total family income of tracts or minor civil divisions for 1969 adjusted for time difference to make it more comparable to 1973 income. c. Median education: Defined as the median years of schooling completed in the tract or township in which the household was located. d. Percent of units owner-occupied: Made up of the percent of units in the neighborhood that were single family dwellings and were owner-occupied. 4. Socialfipsychological factors: Made up of five measures of self-to-others determined to represent accessibility to particu- . laristic resources.. Specifically these were: 15 a. Self-esteem: Defined as a feeling of self-worth in relation to others. b. Social isolation: Defined as a feeling of isolation from group standards. c. Anomia: Defined as a feeling of alienation from society. d. External control: Defined as the belief that the consequences of one's actions are a result of luck, or chance and not necessarily related to the action itself. e. Family effectiveness: Defined as the ability of the family to function as a unit as perceived by the individual members. Assumptions 1. Survey research is an appropriate means of gaining objective and subjective measures related to housing satisfaction. 2. The measures used in this study are valid and reliable. (Reliability will be discussed in Chapter 3). 3. The adult female (or wife) is assumed to be a representa- tive spokesperson for the family's attitudes and beliefs. Hypotheses Ho 1: Satisfaction with housing is related to socio-economic factors, physical housing factors, location factors, and social-psychological factors, each explaining equal amounts of the variance. Ho 2: Socio-economic characteristics are related positively to satisfaction with housing. Ho 3: 16 Family income is related positively to housing satisfaction. Wife's education is related positively to housing satisfaction. Physical housing factors vary in direction of relation- ships with housing satiSfaction by these variables: a. Ownership tenure is related more positively to housing satisfaction than renter tenure status. Single family dwelling type is related more positively to housing satisfaction than other dwelling types. Value per room is related positively to housing satisfaction. Bedroom deficit is related negatively to housing satisfaction. Locational factors are related positively to satisfac- tion with housing. a. Living in rural areas is related more positively to housing satisfaction than living in urban areas. Median income of the area is related positively to housing satisfaction. Median education is related positively to housing satisfaction. The percentage of owner-occupied, single family dwellings in the area is related positively to housing satisfaction. Social-psychological factors vary in direction of relationships with housing satisfaction by these variables: a. Self-esteem is related positively to housing satisfaction. Social isolation is related negatively to housing satisfaction. l7 Anomia is related negatively to housing satisfac- tion. External control is related negatively to housing satisfaction. Family effectiveness is related positively to housing satisfaction. CHAPTER II REVIEW OF THE LITERATURE This chapter focuses on two themes. The first section deals with housing satisfaction literature, particularly that related to intra-urban mobility. This body of literature was felt to be more appropriate than housing satisfaction literature for the present investigation for the following reason. Housing satisfaction liter- ature in general deals with specific aspects of the home and the subjective evaluation of these aspects. In this study, the depend- ent variable was a scale made up of the subjective evaluations in terms of satisfactions with physical attributes of the house. But none of these attributes was examined individually. Rather these attributes or qualities were combined to measure an overall satisfac- tion giving far more depth than a single question on overall satis- faction. The point is that the specific qualities or features that comprise satisfaction were not being studied here. This investiga- tion focused on broader categories of factors that could have affected these subjective evaluations regardless of the objective realities. The mobility literature dealt with these broader cate- gories. In fact, it may well be that movers, present or near future, are better able to express broader areas of dissatisfaction than are nonmovers or those asked to express what they like about their 18 19 houses. Residential mobility literature was more attuned to general areas of dissatisfaction. Since the purpose of this investigation was to examine the relative importance of groups of variables, the mobility literature was far more useful. The second section dealt with specific research done in the areas of the social-psychological variables used in this study as they have not been specifically related to housing satisfaction in the past, but instead to a broader feeling about, or outlook on life. The feeling here was that if these variables were related to satisfaction with life, then they could be related directly to satisfaction with the house. Housing Satisfactions and Dissatisfactions The classic study dealing with mobility and satisfaction is that of Peter Rossi (1955). It examined the mobility patterns of households in Philadelphia. Of those interviewed who were recent movers, 61 percent had moved voluntarily, while 39 percent were considered forced moves caused by evictions, dwelling destructions and intercity migration. Rossi summarized: Among voluntary moves--where the household had a clear voice between staying and moving--the most important factor impel- ling households to move was dissatisfaction with the amount of space in their old dwelling. Other factors in order of their importance were complaints about former neighborhoods and about the costs of rent and maintenance in their old homes (1955, p. 9). In choosing their present homes, the respondents' desires were rank-ordered as follows: space in the dwelling, dwelling design features, dwelling location and cost. However, in the actual deci- sion, cost was paramount. 20 Rossi (1955) also considered a series of household character- istics he felt would influence satisfaction with the present resi- dence, and hence the desire to move. One of these was tenure status. He found a distinct difference between renters and owners with renters having a higher inclination to move. This can be explained in part by the fact that buying a house entails a greater commitment legally and financially than does renting. Involved here is the "axiom of cumulative inertia" (McGinnis, et al., 1963) meaning that the probability of an individual staying in a particular place increases with increasing length of residence. Speare explained in his study of Rhode Island residents: [Cumulative inertia] . . . is the product of various economic and social ties a person has at a particular location. The renter moving into a housing unit has fewer ties. Often his commitment to his landlord can be dissolved with a month's notice . . . . However the process of buying and selling a house involves certain costs and financial risks which rent- ing does not. Thus the homeowner acquires an economic bond to a particular location when he buys a home (1970, p. 452). This extra commitment and homeownership itself have an important effect on satisfaction. Rossi concluded that the very state of ownership produced a certain contentment with the dwelling regard- less of its inadequacies, and what's more this contentment extended to the neighbors and neighborhood. Satisfied persons, especially owners, tended to view their neighbors as homogeneous although this may not have been the case, while dissatisfied persons, especially renters, saw diversity even when it did not exist. Gladhart's find- ings apparently contradict the axiom of cumulative inertia as related to mobility. He suggested a possible explanation: 21 If the mobility of owners . . . is principally dependent upon questions of satisfaction with the current dwelling, then the effect of increased duration in a house may be to increase dissatisfaction with the dwelling until a move is induced (1973, p. 68). In this way time would make matters worse, the small dissatisfactions would mount up until the move is made. Rossi also explained the types of features each family had in mind in the search for a new home (see Table 1). He concluded: The findings of this study indicate the major function of mobility to be the process by which families adjust their housing to the housing needs that are generated by the shifts in family composition that accompany life cycle changes (1955, p. 9). Consistent with this conclusion most researchers have shown that families in the earlier life cycle stages are more apt to have high mobility dependent on family size, age of the head, tenure and tenure preferences, number of rooms and attitudes towards amount of space. Rossi found that space complaints were twice as common for families who had had an increase in family size. In addition, 45 percent of all movers gave space problems as an important reason for moving. Roistacher (1974) found in a recent national survey that "movers are more likely to be the young, selecting home, mates, and jobs, all three of which are searches that tend to settle down with age" (p. 50). The life cycle thesis has been confirmed by Leslie and Richardson (1961) in a study of a Lafayette, Indiana, subdivision which examined association between upward mobility and residential mobility. This study also added the neighborhood or location dimen- sion. The authors concluded that social mobility expectations, 22 TABLE l.--Array of Specifications of Importance to the Families as They Looked for Their New Homes.3 Specificationsb Percentages 1. Specific Dwelling Unit Attributes: Particular space dimensions 51 Particular design requirements (heating, layout, utilities) 50 Costs (rent, maintenance, or purchase price) 19 Other dwelling unit attributes 16 II. Specific Neighborhood Attributes: Social Composition 6 Location 26 Other Neighborhood Attributes 9 III. Other Considerations 5 IV. Vague Considerations 13 V. None ("looking for anything") 5 100% Equals (444) aPeter Rossi, Why Families Move, p. 154 bThe specific wording of the question which elicited the reasons in this table was as follows: "What were the important things you had in mind about a place when you were looking around?" "Other dwelling unit attributes" included such qualities as cleanliness (mainly referring to furnished units), details of con- struction (frame, brick, detached, attached), and so on. "Other considerations" consisted primarily of "availability," e.g., "I needed a place right away and I would have taken anything that was available." "Vague considerations" included such responses as “a better apartment," "nicer neighborhood," etc. In part, the large number of vague responses indicates poor interviewing since such responses should ideally be followed with probes to bring out specific details. But, in large part, the high proportion of such responses indicates the difficulty respondents felt in verbalizing such matters. 23 class differences perceived by respondents between themselves and their neighbors, education and house attitude were highly signifi- cant in relation to mobility and mobility expectations. What's more they found that a family whose social status had changed was more likely to move to a neighborhood or home that better expressed its new status. This finding was substantiated by Chevan in a study of couples in the Philadelphia-Trenton metropolitan area in 1960 (1971). Butler and associates in a national survey of 1500 urban households in 1966-1969, looked at particular housing satisfactions and dissatisfactions. They concluded that number of rooms and number of bedrooms were the most important considerations. They also looked at broader areas of satisfaction and concluded that: Examination of the variation in satisfaction with respect to geographic region, standard metropolitan statistical area size, central city and suburbs, and households of various characteristics shows that dissatisfaction appears to be more common in young households, in larger households, in non- white households, and in households that are renting (Butler, et al., 1969, p. 21). They also concluded that overall dwelling unit satisfaction is most strongly associated with type of dwelling unit and the appearance of the dwellingIhTit,inside and out; and strongly associated with most neighborhood aspects. The group also pointed out that, although more households are dissatisfied with apartments than single-family dwellings, this was partly due to household type liv- ing in apartments. However, Michelson confirmed this hypothesis and found that people living in single family houses on spacious lots evaluated their neighborhood environments more highly than those living in nonsingle family dwelling units (1969). _':T‘ L 24 There is some empirical evidence to indicate that at least at the community level, location of the house makes a difference in the satisfaction, rural residents being more satisfied than urban residents (Marans, and Rodgers, 1972). Fredland (1974) used linear regression models to estimate the influence of a variety of factors on the probability of moving. See Figure 2. He concluded that a family will choose a dwelling that yields optimum satisfaction over as long a period as can be foreseen because of the costs of moving. His results indicated that a lack of sufficient room is highly related to mobility and that mobility is higher in older neighborhoods than elsewhere even when controlling for a variety of other factors. Fredland also found that job changes are not among the principal causes of local residential mobility, although he did find that, for owners, a change of job having the same or higher status raises mobility 3 percent. This appears to support the findings of Leslie and Richardson (1961) that families move in response to career status changes. Fredland did not believe these moves to be in response to commuting considerations. In a synthesis of intraurban mobility, Simmons (1968) con- cluded: The most meaningful aspect of the housing adjustments are the size and facilities of the dwelling unit, followed by the social environment of the neighborhood. The physical site and access to other parts of the city are relatively insig- nificant (p. 637). 25 I = Family income in year t. F = Family demographic characteristics and preference patterns in year t. HUQ = Housing unit quality. HUS = Housing unit size. N0 = Neighborhood quality. LE = Location relative to head's employment. TS = Tenure status (owner or renter). tCP = Cost parameters (e.g. interest, tax rates, insurance costs) in year t. Then for any housing unit (i), for any given family, the annual monetary evaluation of the satisfaction yielded can be explained generally as: tsi = S(HUQi, HUSi, NQi’ LEi’ tF’ tI) Cost is expressed as: CP.) C. = C(HUQi, HUSi, LE1, TSi, t 1 t 1 Net satisfaction with unit(i), in year'(t),tNi becomes: Figure 2.--Model for Viewing the Decision to Move.* *Source: Daniel R. Fredland, Residential Mobility and Home Purchase. 26 Backler (1974), in a study of upper class residential moves in Detroit, found that changes in neighborhood stimulate the deci- sion to move for upper class residents. Bell (1958) studied suburban moves and residence and found "that people with rising income and social status seem highly moti- vated to find neighbors like themselves" (1958, p. 237). Steffans (1964) in a study of North Carolina residents looked at likes and dislikes about previous residences and important considerations in deciding on present neighborhoods. He found that higher income groups were more concerned about the physical char- acteristics of the neighborhood than were other groups. This has been confirmed by Backler (1974). The most important considerations in selecting a future home were rank-ordered as follows: financial considerations; size and character of dwelling; social environment and people in neighborhood; physical character of neighborhood. ¢buono-d Less important were: 1. accessibility of site; 2. physical character of site; 3 availability of services and facilities. Lansing, Mueller, and Barth (1964) found the expressed reasons for plans to move rank—ordered as follows: The house itself, cost considerations, nearness to place of work including occupation changes and neighborhood considerations. Herbert Gans (1967) in his study of the Levittowners con- cluded that house related reasons for moving greatly predominated over community related reasons, and that the need for more space was the primary motive. 27 Greenbie (1969) investigated the relative importance of house and neighborhood in decisions to move in a 1968 study of Madison, Wisconsin, families living in owner-occupied, single- famfily dwelling units. He concluded that the house was more important than the neighborhood. Approximately four out of every ten families would have replaced the house and remained in the former neighborhood had it been feasible. Hartman examined the effects on mental health of forced relocations in Boston's West End. He found that: Among those who liked the West End very much, almost everyone with good housing (98 percent) liked his apart- ment, and only a slightly smaller proportion of those with poor housing (86 percent) liked their apartments. As feelings about the area itself became less positive, however, rates of satisfaction with apartments of compar- able quality decreased. And only then did objective quality of the housing appear to affect attitudes towards the apartment (1963, p. 122). Fish (1974) compared the determinants of residential satis- faction and mobility for high and low income households in homo- geneous and heterogeneous neighborhoods. She found that satis- faction with the house and neighborhood was higher in homogeneous neighborhoods. She concluded that this was due to a higher degree of social organization in homogeneous neighborhoods, and hence less social isolation. Other researchers have examined low income families and found a reasonable degree of satisfaction even in the face of poor housing conditions. In these cases, satisfaction has been associated with attachments to friends and family in the neighborhood (Hollingshead and Rogler, 1963; Suttles, 196B). 28 Foote (1960) in an in-depth investigation into housing choices and constraints found that the two most important motives for moving were the dwelling unit itself and the social qualities of the neighbors. He concluded that the higher the socio-economic status, the higher the contentment with neighbors due to a freer choice to live among neighbors of comparable status. Weiss, Kenney, and Steffans (1966) in a study of the home purchase decision concluded that the quality and character of the homes in the neighborhood was the most important criterion for locational choice mentioned by the respondents. Aligned with this were the findings of Lansing, Mueller, and Barth: Feelings about the kind of people living in a neighborhood and the physical characteristics of the neighborhood are more influential in determining over-all attitudes toward the neighborhood than is convenience of location (1964, p. 34). Foote (1960) indicated that of the movers who complained about their previous neighborhood, half were dissatisfied by its social qualities. These dissatisfactions were related to either real or perceived differences in income, ethnic, racial, or class identi- fication and those of the neighbors. The purpose of this investigation was to examine the rela- tive importance of four groups of factors in determining housing satisfaction. For this reason, mobility literature has been reviewed in hopes of identifying broad categories of satisfaction and dissatiSfaction. Most researchers tie mobility directly to dissatisfaction with some area of housing characteristics (Butler 29 et al., 1969; Butler et al., 1964; Backler, 1974; Rossi, 1955). Rossi identified push and pull factors. "Push" factors tend to create a desire for leaving the present residence and "pull" factors create a desire for living in another location. When the threshold is reached, the move is made (Rossi, 1955; Armiger, Jr., 1960). Rossi identified the "push" factors in order of importance: 1. Dissatisfaction with the amount of space; 2. Complaints about the neighborhood (particularly socially); 3. Cost complaints. However, moving is not always possible as pointed out by Roistacher: Although many families with poor housing quality might desire to improve it, they may be unable to for the very reason that they faced these conditions initially, that is, they have insufficient income to pay for a higher quality dwelling unit (1974, p. 68). In suIrmary, the main cause of dissatisfaction is tied to space constraints within the dwelling related to family_life cycle changes (Rossi, 1955; Roistacher, 1974; Leslie and Richardson, 1961; Butler et al., 1969). Beyond definitive space problems, overall dwelling quality is important. Satisfaction also seems tied to the tenure status of the residents, owners being more satisfied than renters (Rossi, 1955; Speare, 1970). Another area of difference is type of dwelling unit with single family dwellings being most satisfying (Butler et al., 1969; Michelson, 1969). The selection of the home, choice factors involved, alterna- tives available and the ability to satisfy one's material desires 30 in a home are all realted to socio-economic characteristics of the household (Lane, 1972; Roistacher, 1974; Foote, 1961). Neighborhood factors including the social composition of the neighborhood and the fit of the household social status to that of the neighbors has also been identified as being extremely important (Leslie and Richardson, 1961; Chevan, 1971; Fredland, 1974; Backler, 1974). Satisfaction with the neighborhood has also been related to social participation with neighbors (Fish, 1974; Hartman, 1963; Hollingshead and Rogler, 1963). Although factors related to the community or neighborhood and the family's income or education are not directly related to the house itself, it is assumed that they will affect perceptions of housing satisfaction. For example, a family who is entirely satisfied with their house suddenly increases its income substan- tially. Because of the status increase, the very same house may not be so satisfying because the neighborhood is of a lower status than the family feels is appropriate for its increased wealth. This dis- satisfaction with the neighborhood could easily be manifested in complaints about the house itself. Thus satisfaction with the dwelling decreases because of changes in income and perceptions of neighborhood. Perceptions of Self and Effect on Outlook The social-psychological concepts used in this study were an attempt to arrive at an understanding of how one related to those around her/him. 31 Rosenberg (1965) studied the concept of self-esteem among adolescents. He found a statistically significant (.05) association between self-esteem and the appearance of depression. He also found that the lower the self-esteem, the more likely one is to express feelings of unhappiness and discouragement. He concluded that low self-esteem implied self-dissatisfaction (Rosenberg, 1965). In the same way that dissatisfaction with the neighborhood could be expressed in dwelling unit dissatiSfaction, such is the way that self-dissatisfaction could be expressed. In a study of social integration Srole's (1956) findings supported the hypothesis that linked the "individual state of anomia and interpersonal dysfunction in the social realm" (1956, p. 716). Bell (1957) found that anomia is inversely related to economic status and suggested that anomia may result in those who expect economic success and have the least access to it. He concluded: Anomie hsalso related to social isolation. There is wide variability in personal demoralization among urbanites as related to differences in frequency of informal and formal group participation, age and poSition in the class structure. The relationships between neighborhood economic status and anomie suggests that the economic character of the neighborhood population as a unit may play an important part in sorting out persons having different degrees of anomie. It also may directly affect the personal morale of the residents (1957, p. 115). Dean (1961) studied the factors involved in feelings of social isolation. He found that: Residential areas with the highest schizophrenic rates are those characterized by anonymity, spatial mobility, smaller percentage of voting, low social participation, greater unemployment, fewer memberships in lodges and fraternal organizations, more job turnovers, fewer visits from friends, etc. (Dean, 1961, p. 756). 32 Fish (1974) also explored social isolation as a lack of social organization caused in part by neighborhood heterogeneity. Rotter's (1971) investigations into internal-external con- trol, or the beliefs that rewards come from one's own behavior or from external sources, uncovered some interesting findings. Lower- class children are more external while children from richer, better educated families are more internal. Internal and external control, however, also seem related to cultural backgrounds and race as well as to socio-economic characteristics. Rotter also found that external persons feel at the mercy of their environments, being manipulated by outside forces. The last social-psychological measure to be discussed here is that of family effectiveness. In extensive family research, Van der Veen and associates concluded: The parents of less adequately functioning families see their families as being less what they want them to be and are dis- satisfied with more qualities of their families. They see their families as not meeting their hopes and expectations (1964, p. 54). The above social-psychological concepts are meaningful in an individual's general outlook on life and satisfaction with life. Because of this, they are felt to be directly related to outlook on and satisfaction with the housing environment. In the context of the Foas' theory, if in fact these measures do represent accessi- bility to particularistic resources, one would expect a direct relationship between these variables and housing satisfaction. CHAPTER III METHODOLOGY Collection of the Data The data for this study were gathered as part of an inter- disciplinary study entitled, "Functioning of the Family Ecosystem in a World of Changing Energy Availability," funded by the Michigan Agricultrual Experiment Station. This project was a field survey carried out in the greater metropolitan area of Lansing, Michigan, during the months of May and June, 1974. The data used in this study were a small portion of the data gathered for the larger interdisciplinary investigation. The inter- view schedules used to elicit this data were (a) a set of self- administered questionnaires about housing facilities and family; and (b) interviewer-administered questionnaires to gather family demo- graphic data. Data collection for this study also included property tax assessment data gathered from local tax offices; and 1970 census data. The census data used included the published Lansing S.M.S.A. housing data for census tracts and blocks, and the unpublished Fourth Count housing data for minor civil divisions made available through computer tapes. Upon completion of questionnaires and interview schedules, the data were checked by the research team for completeness and 33 34 Individuality of responses. The raw data were transferred to coding sheets by trained coders. All keypunching and verification were done by a commercial firm. Cards were verified further against the raw data. The Sampled Community The sample was selected from the greater metropolitan area of Lansing, Michigan. The Lansing Standard Metropolitan Statisti- cal Area (S.M.S.A.) is considered to be a well-defined social, econ- omic, and political metropolitan area characterized by a diversity of functions. It is the seat of state government, the site of a major university, and the location of light and heavy industry related to the automotive industry. The Lansing S.M.S.A. is a cen- tral area of commercial enterprise surrounded by a productive agri- cultural sector. The Lansing S.M.S.A. has a total p0pu1ation of 378,000 persons and 89,610 families (1970 Census). A multi-stage probability sample of urban, suburban, and rural families was drawn from the tri-county area of the S.M.S.A. Some portions of Clinton, Eaton, and Ingham counties fall within the S.M.S.A. which is considered to be a viable geographic area with a heterogeneous population. Ten census tracts were randomly selected, each tract having a probability proportionate to the number of households therein. Over 600 house- holds were selected from the 34 blocks contained within the ten census tracts by use of the 1973 Polk City Directory. 35 In the rural areas, townships with no incorporated places, and specific sections within townships were selected from the counties in the S.M.S.A. Households were selected from the randomly selected addresses within the sections. Sampling procedures assured attainment of at least 150 urban and 50 rural families. The final sample contained 217 families, 160 urban and 57 rural. A comparison was made between the census data of 1970 for the Lansing S.M.S.A. and the sample to assess the representativeness of the sample. The sample was determined to be closely representa- tive of Lansing S.M.S.A. families (Zuiches et al., 1975). The sample of 217 has since been reduced for the purposes of this study to 198. Elimination of cases was done on the basis of missing data, no wives present in the household, or the wife of the family not serving as the respondent. Description of the Sample Some basic demographic characteristics of the sample (n = 198) are presented in table format. TABLE 2.--Urban-Rural Breakdown of Sample. Category Number Percent Urban 151 76.3 Rural _f§[ ‘ 23.7 198 100.0% 36 Table 2 shows a close correspondence to the desired 150-50 split of the original sample selection. TABLE 3.--Tenure Status of Sample. Category Number Percent Owner 138 69.7 Renter _jfil 30.3 198 100.0% The 69.7% owner-occupied tenure status is very similar to the 1970 Census which shows 62.9% of single family dwellings are owner-occupied in the Lansing S.M.S.A. (U. S. Bureau of Census, 1970. PP. 846-47). TABLE 4.--Structure Type of Sampled Households. Category Number Percent Single family dwelling units 145 73.2 Nonsingle family dwelling units _;g; 26.8 198 100.0% Again this figure is closely related to 1970 Census figures which indicate that 69.4% of dwelling units were single family dwelling units in the Lansing S.M.S.A. (U. S. Bureau of Census, 1970, pp. 846-47). A more detailed description of dwelling type is offered in Table 5. 37 ,TABLE 5.--Dwelling Type of Sampled Households. Category Number Percent Single family 145 73.2 Single family converted to multiple family 3 1.5 Mobile home 12 6.1 Duplex 7 3.5 Four-plex l 0.5 Townhouse 12 6.1 Apt. house 3-10 10 5.1 Apt. house 10-20 3 1.5 High rise __5_ __2;§_ 198 100.0% Selected family characteristics are presented in the follow- ing tables. TABLE 6.--Fami1y Type. Type Number Percent Adults, no children 53 26.7 Oldest child under 12 79 39.9 Oldest child 12-18 33 16.7 Oldest child over 18 _;§i .1941. 198 100.0% As can be seen families in all stages of the family life cycle are represented in the sample with younger families dominating. This information is reinforced by the ages of the wives. 38 TABLE 7.--Age of Wife. Age Number Percent 19-30 75 37.8 31-40 54 27.3 41-50 33 16.7 51-60 25 12.6 Over 60 9 4.6 Missing data __2__ __l;9_ 198 100.0% The following table indicates the range of family income in the sample. TABLE B.--Family Income. Income Number Percent Less than $4,999 16 8.1 $ 5.000-$ 9,999 42 21.2 $10,000-$14,999 59 29.3 $15,000-$24,999 54 27.3 $25,000-$49,999 23 11.6 $50,000 + __g_ 2.0 198 100.0% The median family income of the sample is $13,425 compared to $11,213 for Lansing S.M.S.A. families in the 1970 Census (U. 5. Bureau of Census, 1970). 39 TABLE 9.--Educationa1 Attainment of the Wife. Years Completed Number Percent 0-11 38 19.2 12 years 88 44.4 1-3 years college 37 18.7 4 years college or more i5 __1__7_£ 198 100.0% The median number of years completed is 12.1. As can be seen approximately 80% of the adult females in the sample have at least earned a high school diploma. The high educational attain- ment of the sample may be explained partially by the presence of a large university within the Lansing S.M.S.A. Occupation characteristics are listed in the table below. Both husbands and wives have been included in this table to give a more complete picture of occupational status. The classifications are based on the census occupation classifications. TABLE 10.--Occupationa1 Status of Husbands and Wives. Classification % Males % Females Professional 20.8 17.6 Managerial 10.9 6.8 Sales, clerical 10.9 47.3 Blue collar 45.3 11.5 Service and Household Workers, Laborers 12.0 16.9 (n=192) 100.0% (n=148) 100.0% 40 About half of the male work force have blue collar professions and approximately two-thirds of wives are employed outside the home. Operational Definitions Most of the variables used have been transformed in some way for the purposes of this study. The following discussion will operationally define the variables used in this investigation. Dependent Variable Satisfaction with Housing.--This variable was a scale con- sisting of 15 items. Each item had a possible value from one to five (see Appendix A, page 75). A score of one was given for the highest satisfaction, a score of five was given for the lowest satisfaction. The items in the scale focused on specific physical properties of the housing unit itself dealing with (a) facilities, i.e., size, number, and arrangement of rooms; (b) utilities, i.e., lighting, heating, and plumbing; and (c) environment, i.e., privacy and noise. One item, satisfaction with cooling system, which was originally in the interview schedule, was deleted from the scale because of missing data due to inadequate question composition. Recoding of the values was done such that the highest satisfaction yielded the highest score, the lowest satisfaction the lowest score. Thus the possible low score was 15 and the possible high score was 75. Eleven cases had one item missing from the total of 15. For each of these cases, the mean score of each respondent's scale was used as a substitute. This would in no way affect the 41 statistical outcome of the value of the scale for that respondent. In five more cases, two items were missing. The same procedure was uSed on these cases with the view that in both situations the number of missing cases was small enough so as not to jeopardize the results. A reliability analysis of the final scale yielded a Cronbach alpha coefficient of .8729. As most people tend to be relatively satisfied with their homes, the distribution was not normal, but somewhat skewed as can be seen in the following table. TABLE ll.--Descriptive Statistics on Satisfaction Scale. Mean 57.293 Standard error .649 Median 57.714 Mode 60.000 Standard deviation 9.128 Variance 83.325 KurtoSis .012 Skewness -.152 Range 46.000 Minimum 29.000 Maximum 75.000 Independent Variables Socio-economic Variables.--The two variables used were total family income for 1973 and wife's educational attainment as measures of socio-economic status of the family. Family Income: The data for this variable were gathered into 21 discrete groupings. Then the mid-point of each grouping was used as the total gross family income for 1973. Education of Wife: The data were collected as number of years and type of schooling completed by the wife of the family. 42 These were recoded into number of years only, with technical school- ing such as beauty school and key punch school being coded as one year beyond high school. Physical Housing Variables.--The variables used in this grouping were felt to be measures of housing quality and family fit associated with life cycle considerations. Tenure Status: This variable was used as a measure of owner or renter status and as such defined the family's relationship or commitment to the dwelling unit. It was used as a dummy variable with the value of one given to owners and the value of zero given to renters. Structure Type: This variable was included as a measure of housing quality as well as a measure of housing constraint. It was used as a dummy variable with single family dwelling units being given a value of one and nonsingle family dwelling units being given a value of zero. Only single family dwelling units physically separated from other dwelling units which were permanently located on a plot of land were considered in this grouping. All other dwelling unit types including duplexes, single family homes converted to multiple family dwelling units, apartments, and mobile homes were considered as nonsingle family dwelling units. Although it might be argued that a mobile home has far fewer constraints than an apartment, the nature of mobile home parks is far more con- fining than single family dwelling living. 43 Also it was felt that as a measure of housing quality, single family homes and mobile homes were not comparable. Valuegper Room: This variable was used as a measure of housing quality and was computed differently for owners than for renters. For owners, the procedure was as follows: Two variables were available for total value of the dwelling unit. The first of these variables was obtained from the direct question to the respond- ents, "How much do you think you could get for this house if you wanted to sell it?" There were obvious problems related to the use of these data. The accuracy of the respondent's assessment was dif- ficult to gauge. The other source of data came from local property tax assessments. However, there were also problems with these data. First, the date of the assessment was not collected. A two or three year old assessment compared with a recent assessment would not have reflected true values. What'smore there were many missing values in the assessment data. It was decided to use the first source of data, the respondent's own assessment of the value of her own home. These data were closely checked for obvious flaws. It was discovered that four farmers had given the value of their entire property rather than just that of the dwelling unit. In these instances, and in several cases of missing data, the assessment value (reported to be one-half of the market value) was doubled and used as a substi- tute. This figure for the value of the home was divided by the num- ber of rooms in the dwelling unit to compute the value per room of the dwelling unit. 44 For renters the variable used as the base figure was contract rent per month. This figure was converted to a yearly rent. The yearly rent was divided by the number of rooms in the apartment or house. As such the rental and owner value per room figures were not comparable, the value per room for owners being in the thousands of dollars and the value per room for the renters being in the hun- dreds of dollars. Because of this the value per room for the renters was multiplied by ten as an attempt to make the two groups of fig- ures equitable in the analysis. This procedure has precedent in real estate market assessment for rental property, though is perhaps slightly high for the Lansing area. Bedroom Deficit: This variable examined the fit between the family and the housing space related to life cycle changes. It consisted of a scale developed by Gladhart (1973) based on a bed- room need score. The score was ascertained by computing the number of bedrooms a family would need based on American normative stand- ards for the sharing of bedrooms taking age and sex differences into consideration. The deficit was computed by subtracting the bedroom need score from the number of bedrooms the present dwelling unit actually has. This resulted in a range of scores on either side of zero. A positive score represented an excess of bedrooms, a nega- tive score represented the actual deficit. Social-Psychological Variables.--The variables included in this grouping have been used in previous studies. Their inclu- sion was an attempt to ascertain some of the basic feelings of the 45 individual in relation to others. For reliability coefficients of all measures, see Appendix B, page 81. For this study the wife's scores on all five measures were used as the basis for analysis. Self-esteem: This was a lO-item scale developed by Rosen- berg (1965) to measure the self-acceptance aspect of self-esteem. (See Appendix A.) There were four possible values for each item. Values for all items were added to ascertain the scale score. A high score represented high self-esteem. Social Isolation: This variable was a nine-item scale developed by Dean (1961) as one part of a three part alienation scale to measure alienation from group standards (see Appendix A). The scale was composed of the sum of the nine items presented in standard Likert format with item value ranges from zero to four. A high score represented high social isolation. Anomia; This variable consisted of a five item scale developed by Srole (1956), designed to measure the individual's sense of nelintegration (see Appendix A). This was a Likert-type scale with a range of item values from zero to four. The high summed scale score represented high anomia. External Control: This variable consisted of an 11 item Likert-type scale abbreviated by Valecha (1962) from the original 29-item scale developed by Rotter (1966). It was reduced further by Schiamberg and Morrison (App. A, p. 79). The scale was developed to ascertain the individual's belief in the responsibility for the consequences of one's actions. The scale consisted of eight question 46 pairs using a forced choice format with internal statements paired with external statements. Possible range of scores was zero to eight. High scores represented external control while low scores represented internal control. Family Effectiveness: This variable was a 40-item Likert- type scale originally developed by Van der Veen (1964) and used here in the abbreviated version shortened by Imig (1971). The scale was designed to ascertain the individual's view of her family as a unit. The range of item values was from one to five. After the item values were summed, the higher total scores represented high family effectiveness; the lower scores represented lower family effectiveness. Location Variables.--These variables were included as measures of neighborhood quality. Location: This variable was defined as urban or rural. The urban classification was made up of all persons living in the Lansing urban area, while rural was defined as a location in a township with no incorporated places. The variable was used as a dummy variable with urban being given the value of one, and rural the value of zero. Median Income: This variable represented the median income for each of the 10 tracts or two townShips in which the households were located as reported in the 1970 Census. The purpose was to give an indication of the socio-economic quality of the neighborhood. 47 These figures were adjusted by 1.278 for income and cost of living increases based on census figures for the Mid-Central states (U. S. Bureau of the Census, 1975). Although the rate of increase between the urban and rural areas has not been uniform, the absolute increases were not necessary for the purposes of this study. Median Education: This variable represented the median school years completed for each of the 10 census tracts and two townships in which the sample households were located as reported by the 1970 Census. This variable was also included as a measure of socio-economic quality of the area. Percent Owner-occupied Units: This variable was considered a measure of neighborhood quality. For the urban areas, census block data were used to form neighborhood groupings around sampled blocks. The purpose of these groupings was to account for "the people across the street." No attempt was being made to define neighborhood, instead an arbitrary grouping was delineated composed of various surrounding census blocks. The purpose was to establish very small neighborhoods made up of the blocks contiguous to the sample blocks. These groupings should be more sensitive to indi- vidual housing satisfaction than census tracts. Unfortunately, very sketchy data were available at the block level hence the usage of tract data elsewhere. The criteria for the selection of neighbor- hood groupings are listed in Appendix C. For the rural households, however, this variable was computed at the township level because data at a smaller unit of analysis were not available. 48 Other Variables Considered for Usage Numerous other variables were considered for use in the original conceptualization including race, percent of income spent on housing, length of residence, accessiblity to work, shopping, a cultural measure of need for flexible, diversified housing space, and a plethora of neighborhood or location variables. Most of these were eliminated for reasons of missing data or lack of variation. Most other location variables were eliminated because of too much suppressed data at the township level. A decision was made to keep the rural respondents in the sample at the cost of more location variables. Statistical Analysis Analysis was done by means of CDC 6500 computer using the Statistical Package for the Social Sciences program. As has been mentioned previously, three sets of dummy varia- bles have been used. The purpose of a dummy variable is to show membership in a given category of a variable that cannot be defined as continuous. As used here, all dummy variables are dichotomous. Kerlinger and Pedhazur defined dummy variable as follows: A dummy variable is a vector in which members of a given category are assigned an arbitrary number, while all others--that is, subjects not belonging to the given category--are assigned another arbitrary number (1973, p. 105 . Dummy variables used in this study were: Tenure status (owner = l), renter 0), structure type (single family dwelling = 1, nonsingle 0), and location (urban = 1, rural = 0). family 49 Multiple regression was used in two phases. As an analyti- cal procedure multiple regression was felt to be appropriate because it allows one to examine the collective and individual contributions of independent variables on the variance in a dependent variable. In the first part of the procedure, each group of variables (socio- economic, physical housing, location, and social—psychological) was put into the equation by itself with the dependent variable to get the relative variance explained by each group of variables. Next a multiple regression was done with all variables entered into the equation to get an indication of the contribution of each variable when controlling for all others. CHAPTER IV FINDINGS AND DISCUSSION The results of the statistical analysis are contained in this chapter. The first set of regression analyses was done to determine the relative importance of each group of variables in explaining the variance in housing satisfaction. Each group of variables, socio- economic, physical housing, location, and social-psychological was entered into the regression equation individually. The variance explained, therefore, was for that group of variables only_and did not take into consideration the correlations among variables nor controlling for other variables. Hypothesis 1 indicates the hypothe- sized predicting value for each of the four groups of variables. [ngg Satisfaction with housing is related to socio- economic factors, physical housing factors, location factors, and social-psychological fac- tors, each explaining equal amounts of the variance. Findings The findings of these multiple regression analyses are summarized in Tables 12 through 15. 50 51 TABLE 12.--Regression Results for Socio-Economic Variables with Housing Satisfaction. Probability of Socio-Economic Std. . . b F beta sampl1ng error, Var1ables Error one-tailed test Family income .0002 .00006 9.783 .224 <.005 Education .189 .241 .620 .056 >.75 Multiple R .243 df regression 2. F R Square .059 df residual 195. 6.124 <.025 TABLE 13.--Regression Results for Physical Housing Variables with Housing Satisfaction. Probability of Physical Housing Std. - . F beta sampl1ng error, Var1ab1e Error one-tailed test Tenure 1.028 1.790 .330 .052 >.75 Structure 1.401 1.845 .577 .068 >.75 Value per room .001 .0003 13.375 .245 <.001 Bedroom deficit 2.048 .598 11.719 .236 <.001 Multiple R .392 df regression 4. F R Square .154 df residual 193. 8.753 <.001 52 TABLE 14.--Regression Results for Location Variables with Housing Satisfaction. Location Std. Probability of Variables b Error F Beta sampl1ng error, one-ta11ed test Location -3.771 1.608 5.499 -.177 <.001 Median Income .0006 .0003 6.191 .179 <.001 Median Education 1.495 .606 6.084 .196 <.001 Owner units 3.977 3.224 1.522 .095 <.25 Multiple R .254 df regression 4. F R Square .064 df residual 193. 3.336 <.025 TABLE 15.--Regression Results for Social-Psychological Variables with Housing Satisfaction. Probability of Social-psychological Std. . Variables Error F Beta ggzglg??egr;g:£ Self—esteem -.131 .158 .681 -.061 >.25 Social isolation -.171 .161 1.123 -.083 >.25 Anomia -.753 .466 2.611 -.127 <.10 External control .147 .337 .190 -.033 >.25 Family Effectiveness .148 .078 3.590 .149 <.01 Multiple R .268 df regression 5. F R Square .072 df residual 192. 2.977 <.025 Discussion As is shown in these tables the null hypothesis was rejected. The physical housing varibles epraih 15.4% (R2=.154) of the 53 variance, twice as much as any one of the other groups. The three other groups are closely aligned, however, with social-psychological 2=.072) of the variance, location fac- variables explaining 7.2% (R tors explaining 6.5% (R2=.065) of the variance, and socio-economic factors explaining 5.9% (R2=.059) of the variance. 1 The next multiple regression was done with g11_variables entered into the equation. Table 16 is the result of that. Through- out this chapter standardized regression coefficients will be dis- cussed, because they are felt to be more appropriate for looking at relative contributions of variables. However, the raw betas have also been included in Table 16. Ho 2: Socio-economic characteristics are related positively to satisfaction with housing. a. Family income is related positively to housing satisfaction. b. Education of wife is related positively to hous- ing satisfaction. Findings The findings of this multiple regression analysis using standardized (B) regression coefficients are presented in Table 16. Discussion Both variables are related positively to satisfaction with housing, therefore, the hypothesis is supported. However, the probability of sampling error is great. This suggests that given the other information income and education are not good predictors 54. om.~ .oo. h o.oo om.~ moo. u m.oo op.~ _o. u oo oo.. mNo. u m.ho mm.. mo. u mm mm.. op. u oo o~._ ow. h mu 4 oo_ooh m__oomuzma neocmwgm mo mwmgmmu 8 wow NP no cowuon_gum_v 4 mo mucwoo «poucmogmo .No_ Pooowmae co .m_ ooommozooz Lo oPN. meooom o coo. o opooo.oz .oo.v omm.m a .Fozoso Foo.v moo.o oo_. oko. oo_. mmooo>_ouocco »__5oa m~.x moo. ooo.- mom. oom.- _ogooou _aoemuxm m~.x oFN. omo.- Poo. om~.- arso=< m~.x mop. omo.- mop. ooo.- ooooo_omo Fo_oom mN.A Nooo. Poo. mmr. moo. Emoomo-cpom mm—nmwgw> pmuwmopozohmna puwuom m~.v ooo._ ooo. o-.m ooo.o mo_oo Loozo oooocma moo.v FN_.~ o,_. opo. ooo. ooooouooa cowomz om.x mkm. Boo. mooo. Nooo. usage, =o_omz mN.x 44F. oNo.- Nko.p omo.- oooooooo mmpnm .Eo> cowumuoa _oo.v AMP.m oop. moo. Noo._ oooocoo sootoao Poo.v oom.o mom. oooo. _oo. soot Loo wo_o> m~.A Foe. coo. me.F oom.— waxy moauoogum mN.x omo. ooo. “mo._ oom.P moooom acooap mm_nowgm> mammoo; Foo_mxgo m~.x ooo. Koo. mow. oNo. at?) co oooooooou m~.x _oo. Noo. Noooo. Nooooo. asouoo apoeoa mm—nowgo> uwsocoowuowuom umwu umpoouuwco Locgm .Loggo mcwpooom 4 upon . o mo open Lo soop_ooQOLa oom oooohuoaoow mcwmoo: new: cowuooempuom .m:_m:ox ;u_3 cowuuoemmuom co mo—nowco> acmccoomucu mo mcowuopaggou mgoou—az uco .Loggu moo—658m yo xuwanonogo .mopuome.mgoLLmugovcoum .mucwpuwewmou cowmmocmmmnu.m~ m4m<~ 55 of housing satisfaction. The standardized regression coefficients are low for both variables. In comparison with Table 13, it is interesting to note the great redUction in the F value for family income when controlling for all other variables. ggygg: Physical housing factors vary in direction of rela- tionship with housing satisfaction by these varia- bles: a. Ownership tenure is related more positively to housing satisfaction than renter tenure status. b. Single family dwelling type is related more positively to housing satisfaction than other dwelling types. c. Value per room is related positively to housing satisfaction. d. Bedroom deficit is related negatively to housing satisfaction. Findings The standardized regression coefficients for the physical housing variables are presented in Table 16. Discussion All of the physical housing variables are positively related to housing satisfaction but at differnt levels of sampling error. Tenure and structure type have F's much smaller than the 25 percen- tile level so the probability of sampling error is greater than 25 percent. However, the F levels jump considerably for the other two variables, value per room and bedroom deficit, both of which have probabilities of sampling error much less than .001 percent. This 56 is an interesting finding and suggests that perhaps tenure and structure type are not as valuable as predictors of housing satis- faction as had been assumed. Bedroom deficit, closely related to life cycle changes is an important measure, and value per room is the most important of the group as a measure of housing quality. It must be noted that the positive relationship between housing satisfaction and bedroom deficit is due to the values given the bedroom deficit variable: a positive value signifies a surplus of bedrooms, while a negative value signifies a deficit. There- fore, while deficit itself is related negatively to housing satis- faction, as hypothesized, the variable is related positively to housing satisfaction. All hypotheses are supported. Whether used in the equation by themselves (see Table 13) or in conjunction with all other variables, the value of the physical housing variables as predictors of housing satisfaction is similar. Tenure and structure type are not valuable predictors while value per room and bedroom deficit are valuable predictors. Ho 4: Location variables are related positively to housing satisfaction. a. Living in rural areas is related more positively to housing satisfaction than living in urban areas. b. Median income of the area is related positively to housing satisfaction. c. Median education is related positively to housing satisfaction. d. The percentage of owner-occupied, single-family dwellings in the area is related positively to housing satisfaction. 57 Findings The standardized regression coefficients for the location variables are presented in Table 16. Discussion Median income, median education, and percent owner-occupied units are positively related to housing satisfaction. A negative beta is shown for the location variable which was a dummy variable ,‘eI with rural location equal to zero and urban equal to one. Therefore rural location is positively related to housing satisfaction. The hypothesis is supported. The relative size of the F's is interest- ing to note. Median education seems to be the most important of the variables with a probability of sampling error less than .025. Yet another socio—economic variable, median income has a small F with a probability of sampling error greater than .25. This may mean that as a measure of social status, median education of an area is more valuable than income. By comparing the results of the location variables in Table 16 with the results of the equation in which only the location variables were used as independent variables (Table 14), the dif- ferences are apparent. When controlling for all other variables in the equation, location and median income dropped out as important variables, median education lost in importance somewhat, while the importance of percent owner-occupied, single family dwellings in neighborhood remained about the same. The fact that there was no change in the value of the percent owner-occupied units variable 58 suggests that none of the additional three groups of variables have measured the same dimension of housing satisfaction dealing with neighborhood quality. Ho 5: Social-psychological factors vary in direction of relationships with housing satisfaction by these variables. a. Self-esteem is related positively to housing F”I satisfaction. . b. Social isolation is related negatively to 1- housing satisfaction. ‘ c. Anomia is related negatively to housing satisfaction. d. External control is related negatively to housing satisfaction. e. Family effectiveness is related positively to housing satisfaction. Findings The standardized regression coefficients for the social- psychological variables are presented in Table 16. Discussion As shown by the betas, self-esteem and family effectiveness are related positively to satisfaction with housing, while social isolation, anomia, and external control are related negatively to satisfaction with housing. Thus the hypothesis is supported. Family effectiveness is the most important of these variables in explaining the variance with a low probability of sampling error (<.001). This is an important finding though it seems logical. This variable is the most micro of the five social-psychological 59 variables. It deals specifically with the family, the social unit equivalent to the spatial unit--the house. It seems likely that 'family effectiveness and satisfaction with housing have compatible levels of measurement, i.e., the micro level. None of the other social-psychological variables serve as good predictors of housing satisfaction. An interesting comparison can be made between the value of the social-psychological variables in Table 16 and their values alone as independent variables in Table 15. The most puzzling dif- ference is the change in the direction of relationship of self- esteem to housing satisfaction. In both cases the variable is unimportant as a predictor of housing satisfaction (>.25). The change in relationship could be due to sampling error or measurement problems. In any case the variable seems to merit further investi- gation. When controlling for all_other variables rather than just the social-psychological variables, the F-ratio of family effective— ness jumps noticeably. The F-value for external control also raises slightly while the others decrease. Conclusions By examining the standardized betas and F's in Table 16, the relative magnitude of each of the variables can be ascertained. However, the R square gives the percentage of the variance explained by all the variables in the equation. In this case the equation explains 21% (R2=.216) of the variance in housing satisfaction. 60 This is a relatively low R square as almost 80% of the variance in housing satisfaction is not explained by the variables in the equa- tion. The individual variables used in this equation can be exam- ined more closely by rank ordering them by importance of predictive value when all variables are entered into the equation. This rank ordering is done in Table 17. TABLE l7.--Rank Ordering of Independent Variables by Size of Standardized Regression Coefficient and F-Ratio with Satisfaction with Housing. Satisfaction with Housing Independent Variables Beta F 1. Value per room .235 8.504 2. Bedroom deficit .169 5.137 3. Family effectiveness .169 4.953 4. Median education .118 2.121 5. Percent owner units .095 1.496 6. External control -.O69 .883 7. Structure type .066 .491 B. Tenure status .066 .456 9. Median Income .047 .375 10. Anomia -.039 .219 11. Location -.029 .144 12. Social isolation -.029 .133 13. Education of wife .007 .009 14. Family income .002 .001 15. Self-esteem .001 .0002 61 Of the top five variables the first two are physical housing variables, the third is a social-psychological variable, and the fourth and fifth are location variables. Because the probability of sampling error is high for all other variables, these variables could be artificially increasing the R2 or proportion of the vari- ance explained by the equation. It appears from the F values that only value per room, bedroom deficit, family effectiveness, median education of the area, and percent owner-occupied, single family dwellings in neighborhood are meaningful predictors of housing satisfaction from the 15 variables originally included in the model. CHAPTER V CONCLUSIONS, LIMITATIONS, AND IMPLICATIONS Conclusions This research has attempted to add a new dimension to the study of housing satisfaction, that of subjective evaluation of housing based on feelings, attitudes, and beliefs, in addition to more often used measures such as socio-economic status, locational variables, and physical housing measures. The purpose was to deter- mine the relative importance of each of these groups of variables as predictors of housing satisfaction. The social-psychological measures used dealt with the quality and accessibility of inter- personal relationships. In other words, they were not specifically related to housing, but instead were measures of more general feel- ings about life. It was implicitly hypothesized that general feel- ings about life and relationships with others could be predictive of satisfactions with housing. Other variables included in the equation were socio-economic measures specifically intended to reveal the amount of choice avail- able to a family in its housing selection. The idea is that a wider choice leads to greater satisfaction. Another group of variables included in the analysis was locational or neighborhood variables. Feelings about the area or 62 63 the neighbors are felt to affect feelings about the home. The variables chosen attempted to measure neighborhood quality. The fourth group of variables used in this investigation Vwere general measures of physical housing quality. The findings revealed that as groups of variables, the physical housing variables were the most predictive of housing satisfaction. The other three groups of variables were closely related in their predictive value with social-psychological varia- bles explaining more variance than locational variables, and socio- economic variables being the least predictive. As individual variables the five most predictive in order of importance were: value per room, befroom deficit, family effective- ness, median education, and percent owner occupied units. The findings of this study indicate that housing satisfac- tion is most closely related to specific housing quality attributes. This suggests that in evaluating housing, people, to some extent, are able to separate the house from other facets of life. One measure used for housing quality which was the most predictive was value per room. It is interesting to note that this variable is related directly to dollar value of the dwelling unit yet income essentially is not predictive of satisfaction. This could be due partially to differential spending levels on housing. Another physical housing variable used was bedroom deficit. The values ranged from minus three bedrooms to an excess of four bed- rooms. This variable is tied to changes in family size as part of 64 life cycle stages. This also seems to be a worthwhile measure in predicting housing satisfaction. Both of these measures relating to housing quality can be measured objectively. The other two meas- ures in this grouping, tenure status and dwelling type also can be measured objectively in terms of the differences between renter and owner or single family dwelling and nonsingle family dwelling. But they cannot be ranked in any order without subjective evaluation. In the past single-family, owner-occupied dwellings were the "Ameri- can Dream." Renter tenure status was for the newly marrieds, the transients, and the poor. Apartment or mobile home living was for a similar population. It was assumed that no one with a family or roots in an area would choose to rent or to live in another type of dwelling. However the relative strength of these two variables is not overwhelming. The other phsycial housing variables are far more important. This could be due to changing values and norms within American Society, due to an increasingly mobile society, and due to financial considerations (large capital outlays) involved in buying single family housing. Clearly both tenure and structure type are predictive of satisfaction, but perhaps not as predictive as has been assumed. Median education of the area was the most important location variable. In an urban area with a major state university, the emphasis on education is not surprising. In addition with the large number of families in the eary life cycle stages, there could be a great concern for the educational environment in which the children grow. 65 The location variable next in importance is that of percent owner-occupied, single family dwellings in area. The importance of this variable seems in conflict with the lack of importance of tenure status and structure type. But perhaps this difference can be explained. The importance of living in a neighborhood with a high percentage of owner-occupied, single family dwellings could be a reflection on the neighborhood itself. These types of neighbor- hoods have reputations for being relatively quiet, safe, and uncon- gested. This suggests not that people are satisfied living in owner-occupied, single family dwellings, but instead, are satisfied with living in the types of neighborhoods in which these types of homes are located. In other words, the concern is not with tenure status and structure type for the individual family, but with the type of neighborhood in which these alternatives are available. The importance of median education and percent owner-occupied, single family dwelling units could be due to the large number of young families in the sample. Median income of the area is a relatively insignificant pre- dictor of satisfaction. Ii:appears that social status is more impor- tant than economic status in explaining variance in housing satis- faction. Location is also a relatively unimportant variable. It appears that the location of residence is not of great importance in predicting satisfaction. This suggests that at the level of housing satisfaction urban-rural differences may not be important, 66 but differences could easily show up at the neighborhood or community level not measured in this study. Socio-economic variables came out remarkably low as pre- dictors of housing satisfaction. Neither income nor education have significant relationships to satisfaction. There are some possible explanations of this, especially in view of the much stronger rela- tionship between median education of the area and housing satisfac- tion. The importance of the median education of the area could be totally for the sake of the children in the family, not for the wife's own sake. Therefore, her education could be unimportant in predicting housing satisfaction while education of the neighborhood would be quite meaningful in predicting housing satisfaction. It is interesting that income was not meaningful as a pre— dictor of housing satisfaction although there has been some evidence of this in the literature. Poor people can be just as satisfied as rich people. However, these findings do not support the proposi- tion that choice is related to satisfaction. Clearly the poor do not have the alternatives in housing that higher income families have. They may not have the money or information resources, but yet it appears they can be just as satisfied as the rich. Perhaps lower income people expect less in a house or perhaps they are better able to "make do." It is possible that in terms of housing adjustment behavior discussed by Morris and Winter (1975), the rich either move or remodel, while the poor simply adjust their standards. This seems a plausible explanation. 67 The social-psychological variables explained a small but somewhat meaningful proportion of the variance. Family effective- ness was the most important of these measures and was the third largest individual predictor of all the independent variables in the equation. This is an important finding, and has special impli- cations for behavioral design at the household level. The extent to which the family has to adapt to a housing environment may be related to their family effectiveness and both of these could be tied to changing life cycle stages. The other social-psychological variables used, self-esteem, anomia, external control, and social isolation are relatively unim- portant predictors of housing satisfaction individually. This could be related to the global or broad nature of the four measures. One reason they may not relate to housing satisfaction is that per- haps those with low self-esteem, high anomia, high social isolation who are externally controlled view their homes as sanctuaries from the outside world and from negative reminders of the quality of their lives. For some, perhaps, the house is the only place one is not isolated and alienated. Perhaps once inside, one has to answer to no one but one's family, thus the importance of family effectiveness. Limitations The characteristics of the sampled community should be kept in mind in evaluating the results. The median income and education levels were high. The area is not plagued by racial or ethnic strife or serious overcrowding of housing or high density of population. 68 It might be more frutiful, especially in light of the social- psychological variables, to examine housing satisfaction in an inner city area with a substantial racial or ethnic minority in a larger metropolitan area. It is also possible that some of the measures used could have been weak. Perhaps the satisfaction scale emphasized the physical qualities of the house too heavily, thus the high outcome of physical factors in the regression analysis. It is also plausible that the wife's satisfaction is tied more directly to other family members' perceptions, attitudes, and beliefs. This is suggested by Hogan (1975) who discovered using data from the same study, that a strong relationship exists between wife's self-esteem and husband's values on familism. Perhaps pre- dictors of housing satisfaction are tied to the family as a unit and cannot be ascertained by the use of data from one family member. The neighborhood or location variables could have been expanded and refined by elimination of the rural sample. More and different kinds of neighborhood data would be useful in further analysis. Other variables that might be useful in further analysis include race and racial composition of the neighborhood. Variables dealing directly with family life cycle could be introduced also. In addition, age of the dwelling unit and years of residence might be important predictors. 69 Implications and Suggestions for Future Research The findings of this investigation while interesting were not monentous. Rather than answering the question, what determines or predicts houSing satisfaction, the findings lead to another question: What is it that predicts the other 80 percent of the variance in housing satisfaction? In today's world it is not sur- ’4' prising that only 21 percent of the variance was explained by these I four groups of variables. With the complexity of social and spatial systems in which all individuals function, simple answers no longer suffice. However perhaps a few conclusions are in order. It appears that wives are relatively objective in assessing housing satisfaction based on measures of housing quality and the fit of the family to the house. It seems more physical housing variables would have enhanced the predictive value of the equation. Perhaps more measures of family relationships such as family accessibility to relatives, time spent in the home, a measure of home-centeredness of activities, and closeness of family members would be helpful. Also an in-depth look into family spatial preferences including privacy needs and central family gathering spatial needs would be useful. It appears that satisfaction with housing is assessed at a very micro level; therefore, family level measures would seem most appropriate. Also, perhaps more specific family make-up characteré istics would be appropriate including life cycle information and spread of children's ages. 70 The influence of neighborhood factors on housing satisfac- . tion should not be minimized. They obviously have some effect. Yet perhaps these too should be measured at a far more micro level. Census tracts are too gross a measure of neighborhood quality. Also measures of neighborhood participation could be included. It was stated earlier in this study that most people are satisfied with their homes as measured by the l5-item scale used here. The question must be raised as to the value of housing satisfaction research at the applied level. If the house does serve, in many instances, as a sanctuary or haven in which people feel inherently happy and safe, then perhaps some of the same dimen- sions that comprise this feeling can be infused into other areas of life. Are the aesthetic qualities and the physical properties of the house important? Or is the mode of functioning within the house, of getting along with others in a daily routine more important? Or perhaps the answer lies in the security factor of the home. These are questions raised by this investigation, but not answered by this investigation. The broader question to ask is this: Where does satisfaction with the house fit in relation to other quality of life measures? Perhaps this ranking varies with the amount of sat- isfaction. High satisfaction with housing may cause one to feel it is relatively unimportant in the scheme of life. However, very low satisfaction might change those priorities. In terms of the Foas' theory, no substantive conclusions can be made. However, if one can accept the assumption that family oj-I 71 effectiveness is a measure of accessibility to particularistic resources at a micro level, there seems to be evidence that the Foas' theory may have some merit. It is possible that particularistic resources can only be measured at a more micro level and that perhaps measures dealing with family effectiveness and neighbor and local participation might be more useful in further examination of the theory. In view of the results, and in partial support of the Foas' theory, the amount and quality of interactions in the household and possibly in the immediate neighborhood could be of great impor- tance to housing satisfaction. Therefore, the amount of time spent in the household could be related to housing satisfaction. Thus employment status of the wife might be an important variable to include in future research. At this point in time, perhaps a case study comparison of several families would be useful. Several families who are highly satisfied with their houses and several who are very dissatisfied could be compared on the basis of family characteristics and family functioning as well as neighborhood participation and accessibility to close friends and relatives. This approach might give further insight into the types of family characteristics related to housing satisfaction. At the policy level, satisfaction with houSing should be inherently interesting. In dealing with such problems as housing shortages and housing the underhoused, understanding satisfaction of 72 residents with dwelling units should be the prime goal. But in order to reach that goal, one must be familiar with its components. For this reason research dealing with housing satisfaction is of paramount interest and importance. Perhaps housing programs should go hand in hand with pro- grams designed to improve other aspects of the quality of life, material as well as particularistic. (New and adequate housing by itself will not be enough to solve "housing problems," because housing problems are too closely tied to other problems. The par- ticularistic needs of families may be as important as the material needs. While housing very clearly may be a material resource, its nature and function are so closely related to the exchange of par- ticularistic resources that this dimension must become as much a part of the concept of housing as its physical dimension. APPENDICES 73 APPENDIX A SELECTED QUESTIONNAIRES 74 I5. :83... .3 5.88;“ 3:000 .9 ~95...» 000 338.3. .3250 30.5020 2:. .3 2030.02... on... .mp $30.. 3.0 0:003 05 5 0:0: *0 «.5003 of. .3 1003.8. 5.95:2. of. .2. 02.3.... 0529. 2:. .2 $63503 900.50 2.... .m .9. .02.» .3903 5.030: :5 00.300 $9.03. as... .m $050003 .3320. $30: «20 0005 39.0: 2.... N 35.8.. 2: .o 0:35... 2: .m @500. *0 «0053025 2:. .0 ~aE00. 05 .0 30 as... .n 2800.000 *0 .353: 2:. .N @500. .0 30:5: 2:. .9 0303330 9 8.26:8 2: 8 :03 .0» 332.0 «30 00.30035 0035035 000.30 00:53 . 00:33 «a Y: 0.02.3 2:3 30> 02 >3) 00> 9.0 00:58 301 mpoom cowpooemwpom marmooz 75 76 Ill lllllll § I 0 00.0005 2000.5 Ill lllllll 00.04 .0000 0... E0 . 0.0.... . .000... .< .o. 60.0.. .0 30.0.: .00. 20.3.00 . ...00>E .0. .00000. 0.0... 0.0.. 0.300 . 0...... . 11.11 0.0;... 5.... 00.000. 0.0 . .22.... 0... co Illnlul ...0.>E 0.02.0. 000....0 0.....30 0 00.0. . 1.1111 ..0 000.0 00 0. 000.0 0.0.. .00 00 . .00. . 0.0000 .38 .0 :02. .0 .00.... 00 0. 0.00 .00 . 0.2.0. 0 E0 . ._.0 0. ..< 0000 .0 .0083: 0 0.0.. _ .0... .00. . Illlll .00....000 ...00.0 0. .0000 .000. .0 .....0.... .0 000.00 0 0... .0... .00. . .F 030050....» 00.2.2.0. 0... .0 00.. 0000 00 mqm .3. x0000 0.00.0. 6.00.030: 00.2.2.0. 0... 0...... 00.0.3.0 .0 00.00 00.. .0000... .50.. 0.00.00. 0. 00.. 00... .500 0.00.... 02. 000...-..0m 77 00.0020 2000.5 0200.5 0.0..0003 00.0< 00.0< 2000.5 .00 .0000 000 0.. ...0...... 2.00.... >..00. .00 .000 00..00 0 .>00 0.0.. ._. 0.0.0. 0... .0. ..00. .00.... >02. 0... 0...... 2.0.5 0... 0.0. 00.0....0 02.0 0. ..0. >.0.0.. .. .. 00..00 .00 0202. 00.200 .. 005 000.050 0.... .0 .0. 0... .>0. 0.0000 0.00. .002. .0 8.0. 0. ...0... .0 0.00 000. 5000.00. .0. 000 >000. .0. ..00... >..0.0 0.... 0. .0.. 00..00 0 .>0002.02 .00... 000.050 0... .0 .E0.00.0 0... 0. 02.0.0.0. >..00. .00 0.0 08.0 >0... 0.00000 ..0.0...0 0:000 0. 00.....5 0. 0.0 0...: ..0.0..._. ...00:00. .00> 0. 00.0.0000 2.0.00 .00....000 m 0... .0 ..000 .0. 0000. a .\.. 200:0 0.00.0. 000.323. 0... .0 ..000 ....2. 00.00 00> 00 ..000. 2.0... ..00... 0:000 00.0.000. 3000.38. 0.00. 0.0 .5200 0.Eoc< 78 0200.5 >.000..m .0000 0 000.0 00.0020 0.0..000... 00.0< 00.0< 2009.0 .0.... >..00. 0.. .0 03.0 .0 .000... ...... 0. .00 .00 00 . ..0. .20.. 000 >.000... 2.05.00 ..0. 0.0 0.0000 0.0... >00 0.0000 0003.00 .0.. 0.00000000 2.0. 0.0 0.0.. b 000.0 >.000... 0 >..00..00 .. 0.... 0.5 ..0...2. 0. 0:02. 0.... .0.... >..00. 0.. .0 03.0 .0 .000... >0 .00 02.50. .00 .00 00 . ..050 .0 00.. 0. >.00 .0 0.0 .000... .00... .2002 .00. 0.00.0. >000. 0.0000 ..0.... >.000... ..0.0.... .26... 0.. .. .000... 00.. .>0.5.0 000 000 .0003 0... 0. 000.0 .00. . .0.....00.0m ..00..00. .00> 0. 00.0.0000 2.0.00 .00...000 0 0... .0 ..000 .0. 0000. «ad. 0. .3. 0.00.0. 00:52.0. 0... 5.2. 00.00 00> 00 ..00... .50.... .>000. 0.0000 .0000 ..00E0.0.. 00.0. 0.0 2.200 00..0Pom. .0.0om 79 External Control Below are some stetemmts about public and private concerns. Please check M & answer that you agree with more for each of the following ms of statements. There is no right answer, just check (Vi either 1 or 2, according to how you feel. . 1. a. __ Many of the unhmpy things in people's lives are partly due to bad luck. b. _. People's misfortunes result from the mistakes they make. 2. a. __ The average citizen can have an influence in government decisions. b. _.. This world is run by the few people in power, and there is not much the little guy can do about it. 3. a. _ When I make plans, I am almost certain that I can make them work. _ It is not always wise to plan too far ahead because many things turn out to be a matter of good or bad fortune anyhow. 4. a. _ As far as world affairs are concerned, most of us are the victims of forces we can neither under- stand, nor control. b. __ By taking an active part in political and social affairs, the people can control world events. 5. a. _ There really is no such thing as ”luck". b. __ Most people do not realize the extent to which their lives are controlled by accidental happenings. . __ With enough effort we can wipe out political corruption. b. __.~ It is difficult for people to have much control over the things politicians do in office. 7. a. __ Many times I feel that l have little influence over the things that hmpen to me. b. ._ It is impossible for me to believe that chance or luck plays an important role in my life. . __ What happens to me is my own doing. b. _ Sometimes I feel that I do not have enough control over the direction my life is taking. The ll-item scale reduced by Valecha has been further reduced for the purposes of the larger interdisciplinary study by Dr. Lawrence B. Schiamberg and Dr. Bonnie M. Morrison, members of the research team. 80 Family Effectiveness Please answer the following statements as they relate to your family. Please check lvf the blank which best fits your feelings for each of the following a questions. Strongly No Stronfly Agree A'ee Opinion Disagree Disagree 1. Little problems often become big ones 2. We are a strong competent family. __ __ __ __ _ 3. Accomplishing what we want to do seems to be difficult. _ .— 4. There are many conflicts in our family. __ 5. Each of us wants to tell the other what to do. —. _. —_ _ 6. We often praise or compliment each other. _. __ 7. We encourage each other to develop in his or her own individual way. __ __ 8. Usually each of us goes his own separate way. .— 9. We tend to worry about many things. __ __ __ 10. We sometimes wish we could be an entirely different family. ._ _. __ 11. We respect each other's privacy. __ __ __ 12. We do not understand each other. 13. Our decisions are not our own, but are forced on us by others. __ , 14. We.- get along very well in the com- munity. _ _ ..— 15. There are serious differences in our standards and values. __ __ 16. We do not like each other's friends. __ __ 17. The family has always been very im- portant to us. __ — 18. We resent each others outside activities. __ __ 19. We are a disorganized family. __ __ __ 20. We do many things together. __ _ __ ___ APPENDIX B RELIABILITY COEFFICIENTS 0F SOCIAL-PSYCHOLOGICAL SCALES BI Reliability Coefficients of Social-Psychological Variables Chronbach's Alpha Self-esteem .864 Anomia .766 External control .686 Family effectiveness .911 Unequal-length Spearman-Brown Split Halves Social isolation .036* *In the original study by Dean (1961), this reliability coefficient was .84. It appears the use of this scale with the present sample popula- tion is questionable. 82 APPENDIX C CRITERIA FOR NEIGHBORHOOD GROUPINGS 83 CRITERIA FOR NEIGHBORHOOD GROUPINGS l. Blocks across the street from sample families are included unless street is a main thoroughfare (usually four lanes or more). 2. At least one block on each of two sides of the sample block are included. 3. If the block is smaller than surrounding blocks, all surrounding blocks are included. 4. Blocks surrounded by sample blocks are included. 5. If the sample block is physically much larger than the average blocks because it is less developed or newly developed or is relatively rural, block alone is used as neighborhood. 6. Odd-shaped blocks that fit into spatial divisions are included. 7. If two blocks or less separate two sample blocks, the blocks are combined into one neighborhood grouping. 84 APPENDIX D CORRELATION COEFFICIENTS OF VARIABLES 85 HOUSATIS VARIO7 VAR305 VAR450 VAR452 VAR454 VAR456 VAR458 TENURE DNELTYPE VALU BEDDEF LOCATION MEDINCOM MSCHOOL OWNER Variable Labels Housing Satisfaction Scale Family Income Education of Wife Self-esteem Social Isolation Anomia External Control Family Effectiveness Tenure Status Structure Type Value per Room Bedroom Deficit Location Median Income of Area Median Education of Area Percent Owner-occupied, Single-Family Dwelling Units in Neighborhood 86 87 no« can ova can wow cow cow mmfi cm« and oma cow owe nma cod .cmd mmmwn omqozh4wzo 34¢) wmazmh omsa<> om3¢<> 4m414> Nme<> omamd> mamm<> nodd<> mnhqmaoz uqdem<> 88 umoomm dame. amwuo came. nosuos wa>b4w2a camoNo nun-oar Noose. scamwor unhumo 34¢) aNQaNos ctnudo swoune anamoei «h:oeo «mono. wxazwh msoowo concoct sauna. onaowes Jammwe cocoo- omuooos cm:a¢> mswwaos 00009.0 soswe. amo~aoo amuse. mammoos canon. mwnsaos mm:¢¢> Gamma. ocm:oot «moooor :oeoaos «wsoaat s:a:«. hMNmn. cash“. Noscmos :m:~¢> Noomao odtudor :Nonooi adamooi cahanor odoho. coduaor ~3nsa. ncas~or Leann. ~m3m4> sense-r «swan. Loo:o. comma. :hnoaoi mosmaer nmwoaos ¢usawor aNLMnar mnmoao onmon. amsmc> ouomaor edema. oosmaor Nowmeo ouwooer csANAei onmmdar omsmoor semen. mnmoaos oooedes ammn~os Joozumt mm:~:as waned: amocwer caduwo :noooo Nance. comma. nnanuas oo:a~. aoooaet seducet owonues :aomner nsnuuer :Ooaoo 3o~woar T‘-‘ oo~«o. snudd> oun:a.s cocoa. hssdn. mmmsa.r «mood. NANNM. scum:o ocoon. «mama. owmeoos unmade! ocmmuot commas- moonw- oaupamtou mm awthdt Mu coma-com no u34¢3 4 :ouznamt tauhCQOJ masonat onuome MNNJNo- wuhcmaoz manna. sowed. msnnaa mummoos «meow. doom“. msonuo unmade m-n~o sonuues noaouat dogmaas ”sown. nomad. soon~o dwxso 40020”! zoozuawt duzxo 400:0”: toquawt Zeubcooa mwaauo wobbJuao 341’ wdazmh omodda omolca omaudr umo¢¢> amclc’ nomad: soddct hozzco b2m~0umuwcu < um .mrzwuunuuwoo ScubCJuddoo BIBLIOGRAPHY 89 BIBLIOGRAPHY Abu-Lughod, Janet, and Foley, Mary Fix. "The Consumer Votes by Moving." In Urban Housing, pp. l75-9l. Edited by William Wheaton, Grace Milgram, and Mary Meyerson. New York: The Free Press, 1966. Armiger, Jr., Louis E. Toward a Model of the Residential Location Decision Process: A Study of Recent and Prospective Buyers of New and Used Homes. Environmental Policies and Urban Development Thesis Series, No. 5. Chapel Hill: Center for Urban and Regional Studies, l966. Backler, Alan L. A Behavioral Study of Locational Changes in Upper Class ResidéntiaT'Areas. Geographic Monograph Series, Vol. 5. Bloomington, Indiana: Department of Geography, Indiana University, 1974. Baggaley, Andrew R. Intermediate Correlational Methods. New York: John Wiley & Sons, Inc., 1964: Bell, Wendell. "Anomie, Social Isolation, and the Class Structure." Sociometry 20 (1957): 105-16. . "Social Choice, Life Styles, and Suburban Residence." In The Suburban Community, pp. 225-47. Edited by William M. Dobriner. New York: G. P. Putnam's Sons, l958. Beyer, Glenn. Housing and Society. New York: The MacMillan Company, 1965. Brown, Lawrence A.; Horton, Frank E.; and Wittick, Robert I. "On Place Utility and the Normative Allocation of Intra-Urban Migrants." Demography 7 (May, 1970): 175-83. Butler, Edgar W.; Chapin, F. Stuart, Jr.; Hemmens, George 0.; Kaiser, Edward J.: Stegman, Michael A.; and Weiss, Shirley F. Moving Behavior and Residential Choice: A National Survey. National CooperatiVe Highway Research Program Report No. 81. Washington, D.C.: National Research Council, 1969. Butler, Edgar W., and Kaiser, Edward J. "Predictions of Residential Movement and Spatial Allocation." Urban Affairs Quarterly 6 (June, 1971): 477-94. 90 91 Chao, Lincoln L. Statistics: Methods and Analyses. New York: McGraw-Hill Book Company, 1969. Chevan, Albert. "Family Growth, Household Density, and Moving." Demography 8 (November, 1971): 451-58. Dean, Dwight G. "Alienation: Its Meaning and Measurement." Ameri- can Sociological Review 26 (October, 1961): 753-58. Dewey, Richard. "Peripheral Expansion in Milwaukee County." Ameri- can Journal of Sociology 54 (January, 1948): 118-25. Fish, Gertrude. "Residential Homogeneity and Neighborhood Satis- faction." Housing Educators Journal 1 (May, 1974). ‘Foa, Uriel G., and Foa, Edna B. "Measuring the Quality of Life: Can It Help Solve the Ecological Crisis?" International Journal of Environmental Studies 5 (1973): 14—28. Foote, Nelson N.; Abu-Lughod, Janet; Foley, Mary Fix; and Winnick, Louis. HouSing_Choices and HouSing Constraints. New York: McGraw Hill Book Company, Inc.. 1960. Fredland, Daniel R. Residential Mobility and Home Purchase. Lexington, Massachusetts: D. C) HeathTE Company,TT974. Gans, Herbert. The Levittowners. New York: Pantheon Books, 1967. Gladhart, Peter M. "Family Housing Adjustment and the Theory of Residential Mobility: A Temporal Analysis of Family Resi- dential Histories." Ph.D. dissertation, Cornell University, 1973. Greenbie, Barrie Barstow. "New House or New Neighborhood? A Survey of Priorities Amon Home Owners in Madison, Wisconsin." Land Economics 45 (August, 1969): 359-65. \Hartman, Chester W. "Social Values and Housing Orientations." Journal of Social Issues 19 (April, 1963): 113-31. Hogan, Jan. "Energy Conservation Ethic: Family Values, Practices, and Contextual Variables." Ph.D. dissertation, Michigan State University. In Progress. Hollingshead, August B., and Rogler, Lloyd H. "Attitudes Toward Slum and Public Housing in Puerto Rico." In The Urban Condition, pp. 229-245. Edited by Leonard Duhl. New York: Basic Books, 1963. 92 Imig, David R. "Masculinity-Femininity as Related to Family Marital Adjustment." Ph.D. dissertation, Michigan State University, 971. Kerlinger, Fred N., and Pedhazur, Elazar J. Multiple Regression in Behavioral Research. New York: Holt, Rinehart and Winston, Inc., 1973. Lane, Sylvia. "Housing the Underhoused." Unpublished report on research directed by Fred Case. Los Angeles: Univeristy of California, 1972. (Mimeographed) Lansing, John 8.; Clifton, Charles Wade; and Morgan, James N. New_ Homes and Poor Pe0p1e. Ann Arbor: Survey Research Center, Institute for Social Research, 1969. Lansing, John, and Mueller, Eva, with Barth, Nancy. Residential Location and Urban Mobility. Ann Arbor: Survey Research Center, Institute for Social Research, 1964. Leslie, Gerald R., and Richardson, Arthur H. "Life Cycle, Career Patterns, and the Decision to Move." American Sociological Review 26 (December, 1961): 894-902. Lively, C. E., and Tauber, Conrad. Rural Migration in the United States. Research Monograph 19. Washington, D.C.: U. 5. Government Printing Office, 1939. Marans, Robert W., and Rodgers, Willard. “Toward an Understanding of Community Satisfaction." A paper prepared for the National Academy of Science Panel on the Significance of Community in Metropolitan Environment. thuiArbor: Institute for Social Research, 1972. (Mimeographed) McAllister, Ronald J.; Kaiser, Edward J.; and Butler, Edgar W. "Residential Mobility of‘Blacks and Whites: A National Longitudinal Survey." American Journal of Sociology 77 (November, 1971): 445-56. Mehrens, William A., and Ebel, Robert L. Principles of Educational and Psychologjcal Measurement. Chicago: Rand McNally & Company, 1967. Michelson, William. "Analytic Sampling for Design Information: A Survey Of Housing Experiences." In EDRA I. Edited by H. Sanoff and S. Cohn. Proceedings of the First Annual Environmental Design Research Association Conference, 1969. 93 Michelson, William; Belque, David; and Stewart, John. Intentions and Expectations in Differential Residential Selection. Ottawa: Center for Urban and Community Studies, UniVersity of Toronto and Ministry of State for Urban Affairs, 1972. Morrison, Denton E., and Henkel, Ramon E., eds. The Significance Test Controversy:-A Reader. Chicago: Aldine Publishing Company, 1970. Morris, Earl W., and Winter, Mary. "A Theory of Family Housing Adjustment." Journal of Marriage and the Family 37 (February, 1975): 79-88. Robinson, John P., and Shaver, Phillip R. Measures of Social Psye chological Attitudes. Revised Edition. Ann Arbor: Survey Research Center, Institute for Social Research, 1973. Roistacher, Elizabeth. "Residential Mobility." Chapter 2 in Five Thousand American Families--Patterns of Economic Progress, 41-77. Volume 11. Edited by James N. Morgan. Ann Arbor: Survey Research Center, Institute for Social Research, 1974. Rosenberg, M. Society and the Adolescent Self-Image. Princeton: Princeton University Press, 1965. Rossi, Peter. Why Families Move. Glencoe, Illinois: The Free Press, 1955. Rotter, Julian B. "External Control and Internal Control." Esy: chology Today, June, 1971, pp. 37, 38, 40-42, 58, 59. Rotter, Julian B. "Generalized Expectancies for Internal Versus External Control of Reinforcement." Psychological Mono- graphs 80 (1966) No. 1. (Whole No. 287) Sabagh, George; Van Arsdol, Jr., Maurice D.: and Butler, Edgar W. "Some Determinants of Intrametropolitan Residential Mobility: Conceptual Considerations." Social Forces 48 (September, 1969): 88-98. Schorr, Alvin L. Slums and Social Insecurity, U. S. Department of Health, Education, and Welfare, Social Security Administra- tion, Division of Research and Statistics, Research Report No. 1. Washington, D.C.: U. S. Department of H. E. W., 1973. Simmons, James W. "Changing Residence in the City: A Review of Intra-Urban Mobility." Geographical Review 58 (October, 1968): 622-51. 94 Speare, Jr., Alden. "Home Ownership, Life Cycle Stage, and Resi- dential Mobility." Demography 7 (November, 1970): 449-58. Srole, Leo. "Social Integration and Certain Corollaries: Explora- tory Study." American Sociological Review 21 (December, 1956): 709-16. Steffans, Roger. Factors Influencing,Consumer Choice of Residential Location. Environmental Policies and Urban Development Thesis Series No. 3. Chapel Hill: University of North Carolina, 1964. Suttles, Gerald D. The Social Order of the Slum. Chicago: Univer- sity of Chicago Press, 1968. U. 5., Bureau of the Census. "Consumer Income." Current Population Reports, Series P-60, No. 97, January, 1975. U. 3., Bureau of the Census. Fourth Count, File B Tape File for Minor Civil Divisions, Population and Housing. Washington, D.C.: U. S. Department of Commerce, 1971. U. 5., Bureau of the Census. Housing, Volume III, Block Statistics. Washington, D.C.: U. S. Department of Commerce, 1971. U. 5., Bureau of the Census. Population and Housing, Census Tract Reports. Washington, D.C.: U. S. Department of Commerce, 1971. Valecha, G. K. "Construct Validation of Internal-External Locus of Control as Measured by an Abbreviated 11-Item IE Scale." Ph. D. dissertation, The Ohio State University, 1972. Van der Veen, Ferdinand. "The Parent's Concept of the Family Unit and Child Adjustment." Journal of Counseling Psychology 12 (Summer, 1965): 196-200. Van der Veen, Ferdinand; Huebner, B.; Jorgens, Barbara; and Neja, Jr., P. "Relationships Between the Parents' Concept of the Family and Family Adjustment." American Journal of Ortho- psyghiatry 34 (January, 1964): 45-55. Weiss, Shirley F.; Kenney, Kenneth B.; and Steffans, Roger C. "Consumer Preference in Residential Location: A Preliminary Investigation of the Home Purchase Decision." Research Previews 13 (April, 1966): 3. Zuiches, James; Morrison, Bonnie M.; and Gladhart, Peter. On Inter- viewing Families, Methodology and Design of "Energy and the Family" Survey. Occasional Paper No. 2, Project 3152, "Functioning of the Family Ecosystem in a World of Changing Energy Availability." Institute for Family and Child Study, College of Human Ecology. Michigan State University, April, 1975. "7111111 11111117111111 ITS