SOME DETERMINANTS OF COMMUNICATION NETWORK CHARACTERISTICS AMONG CLOSE FRIENDS Thesis for the Degree offM. Ag. MICHIGAN STATE UNIVERSITY MALCOLM} R, PARKS . "~ 1975 :- - ”wt” ' ? \ BINDING BY v ‘1‘ IIIJAE & SONS' BIIIIK BINDERY INC. LIBRARY BINDERS SPIIIEPOII..IIICIIGAI MSU LIBRARIES .-:_. RETURNING MATERIALS: PIace in book drop to remove this checkout from your record. FINES will be charged if book is returned after the date stamped below. ABSTRACT SOME DETERMINANTS OF COMMUNICATION NETWORK CHARACTERISTICS AMONG CLOSE FRIENDS BY Malcolm R. Parks The research sought to develop and test a model which would predict the size and integration of communication networks among close friends. The nature and significance of close friendship as a unique class of social relations are examined. An extensive review of literature led to the development of a causal model which attempted to predict network size and integration on the basis of a combination of individual, situa- tional and environmental variables. Network size was hypothesized to be a function of the desire, abil- ity or skills and opportunities for participation in close friendship communication networks. Opportunity was conceptualized as the common factor among the following underlying variables: 1) residential mobil- ity; 2) the number of memberships in voluntary associations; 3) the sub— ject's socioeconomic status; A) the amount of time spent with mass media sources; 5) the amount of time spent with non-friends; 6) the amount of time spent with non-close friends; and 7) the amount of time spent alone by the subject. The analysis of zero—order correlations of these vari- ables with network size indicated that only the amount of time spent alone was significantly related to network size. This was a negative association. When desire, skills, and opportunity were entered into a multiple regression equation to predict size, only opportunity proved to Malcolm R. Parks be related to size at a level of statistical significance. This was a positive relationship. Network integration was hypothesized to be a function of four vari— ables. These were: 1) the overall level of perceived similarity among members; 2) the overall level of effort necessary for members of the net— work to communicate with each other; 3) the level of the subject's residen— tial mobility; and 4) the size of the communication network. An analysis of the zero—order correlations and multiple regression procedures indicated that the only statistically significant predictor of integration was per— ceived effort. The entire model was tested within a path analytic format. Because of the lack of proper software, a substantial amount of the final aspect of the analysis was achieved by means of relatively crude improvised pro- cedures. As a path analytic model, the causal model received little sup- port. In general, the hypothesized relationships among the variables did not explain any significant portion of the variance. The major problems which such procedures and results are discussed in detail. In addition to hypothesizing and testing a general model of network characteristics, a secondary goal of the research was to secure descrip— tive information regarding the nature of close friendship networks. It was found that such networks tend to be relatively small (Mean Size = 7.91 persons) and quite poorly integrated. The implications of this latter finding for the application of small group research and theory to friend- ship relations are discussed. Finally, the research is criticized in terms of the use of a student sample (N = 58), measurement, and conceptualization. The implications for future research are explored. 75m) //'7 SOME DETERMINANTS OF COMMUNICATION NETWORK CHARACTERISTICS AMONG CLOSE FRIENDS BY Malcolm R. Parks A THESIS Submitted to Michigan State University in partial fulfillment of the requirements for the degree of MASTER OF ARTS Department of Communication 1975 Accepted by the faculty of the Department of Communication, College of Communication Arts, Michigan State University, in partial fulfillment of the requirements for the Master of Arts degree. fizz/113d OT) 27724ng Director of Thesis Guidance Committee: IZZIZMé'é (ZI Z ZK/éf/t , Chairman Kig/ :zém:j/.Jdmc ACKNOWLEDGMENTS A large number of persons generously contributed their time, effort, resources and insight to this research. Drs. Gerald R. Miller, Richard V. Farace and Edward L. Fink gave willingly of their skills and experience in their capacity as my guidance committee. Dr. Fink was especially helpful in assisting me with design and analysis considerations. In addition to their excellent assistance on theoretic issues, Drs. Miller and Farace generously provided resources for the study. I would like to especially thank Dr. Miller for his ex- penditure of time and energy in the role of committee chairman. Several of my colleagues served as resource persons, sounding-boards and critics. Among these persons are Mark Miller, Mark Milkovich and Dave Seibold. I would like to especially thank John Marlier and Frank Boster. John lended insight into almost all aspects of the research. Frank's continual pessimism was a major source of inspiration. Norm Fontes was especially generous in giving me insight and helping me to secure resources. Finally, I would like to thank my wife, Jody, who tolerated my be- havior during the time I was conducting the research. She also devoted countless hours to the tedious task of preparing questionnaires. I owe whatever insights may be derived from the study to these in- dividuals. I have been fortunate to be surrounded by talented, resource- ful and insightful persons. Its faults are my own. ii TABLE OF CONTENTS Page Chapter I THE RESEARCH PROBLEM: A REVIEW OF THE LITERATURE ............ l The Nature and Significance of Close Friendship.... ...... . 1 Communication Networks ........ . ......................... .. 7 Network Size.. ...... ........... ....................... . 9 Network Integration .............................. . ..... 10 Hypothesized Determinants of Network Characteristics ...... 1n Determinants of Network Size........ ............ ....... 1n Determinants of Network Integration.. ................. . 19 A Causal Model of Determinants of Network Characteristics............ ..... ..... ............... 25 II METHODS AND PROCEDURES. .......... ......... ........ . .......... 28 Selection and Description of the Sample..... .......... . 28 Data Collection Procedures............................. 29 InstmmentationOOOOOOOO0.0.0.0000...OOOOOOOOOOOOOOOOOOO 3]- Reliability of Measurement ......... .. ..... ............. 38 III RESEARCH FINDINGS.............. ....... ....................... #1 Descriptive AnaIYSiSOOOOOOOOOOO0.0.00.0.0.000.000.00.00... ”l Deteminants Of Network Size....OOOOOOOOOOOOOOOOOOOOOOO ”l Determinants of Network Integration.................... A7 Analysis of Zero-Order Correlations....................... 49 Determinants of Network Size........................... #9 Determinants of Network Integration.................... 55 Multiple RegreSSion AnalYSiSOOOOO0OOOOOOOOOOOOOOOOOOOOO... 57 Deteminants Of Network Size.....OOOOOOCOOOO00.0.0.0... S7 Determinants of Network Integration. ........ ........... 59 iii Chapter A Path Analytic Evaluation of the Causal Model .......... . IV SUMMARY AND DISCUSSION ...................................... Summary of Findings ...................................... Descriptive Analysis .................................. Analysis of Zero-Order Correlations ................... Multiple Regression Analysis .............. . ........... Path Analysis ......................................... Implications and Suggestions ............................. LIST OF REFERENCES ................................................. APPENDICES Appendix I WAVE #l. ................... . ............ . ................... II WAVE #2.. ............. . .......... ....... .................... III WAVE #3.. ..... ..... ..... .... ................. . .............. IV WAVE #H...... ............................................... V DATA TRANSFORMATIONS ................ ...... ........ . ......... VI PROCEDURES FOR THE ESTIMATION OF OPPORTUNITY...... ...... .... VII PROCEDURES FOR THE ESTIMATION OF PATHS FROM OPPORTUNITY TO UNDBRI‘YING VARIABLES...OOOOOOOIOOOOOOOOOOOOOO0.00......O. VIII PROCEDURES FOR THE ESTIMATION OF THE RELATIONSHIP BETWEEN PERCEIVED SIMILARITY AND INTEGRATION..................... iv 6O 65 65 65 68 69 71 72 77 84 108 120 121 Table LIST OF TABLES Summary of Differences Between Friendship and Non— Friendship............... ............................... Summary of Differences Between Close Friendship and Non-Close Friendship.... ................................ Test-Retest Reliability Estimatesa ......................... Descriptive Statistics for Variablesa ...................... Intercorrelations Among and Descriptive Statistics for variablesa. O C OOOOOOOOOOOOOOOO O O O O OOOOOOOOOOOOOOOOOOOOOOO Intercorrelations Among Exogenous Variablesa ............... Skewness of Variables and Their Logarithms................. Regression Coefficients for Variables Underlying Opportunity..................... ........ ..... ......... .. Estimates of p21................. ..... ..................... Page 39 42 50 59 117 119 124 LIST OF FIGURES Figure Page 1 Hypothesized Causal Model of Network Characteristics and Their Determinants ............................... 27 2 Model Indicating the Pattern of Zero-Order Correla— tions Among Variables ......... . ...................... 51 3 Model Indicating the Pattern of Regression Coeffici- ents Among Major Variables ........................... 58 H Hypothesized Model Cast into Path Analytic Format ....... 63 vi CHAPTER I THE RESEARCH PROBLEM: A REVIEW OF THE LITERATURE From the social milieu, we select persons with whom we communicate. As a result of the fact that some persons are selected and others are not, networks of communication evolve. The present research deals with the characteristics and determinants of an important class of communication networks—-those among close friends. The chapter progresses in three parts: 1) a brief examination of the nature and significance of close friendship; 2) a description of communica— tion networks and an identification of their relevant characteristics; 3) the identification and explication of those variables hypothesized to be determinants of close friendship communication networks. The Nature and Significance of Close Friendship In almost all societies individuals form friendships (Cohen, 1961). The topic of friendship has been a perennial one in the literature of Western civilization (Cohen, 1961; Rake, 1970). Despite the ubiquity and significance of friendship, most observers (Albert 8 Brigante, 1962; Rangell, 1963; Fiebert 6 Fiebert, 1969; Sadler, 1970; Simon, Crotts 8 Mahan, 1970; Weinberg, 1970) agree that relatively little social scien- tific attention has been devoted to its study. Close friendships serve important and highly valued functions. How- ever, relatively little research has been directed toward the explication of these functions (Armstrong, 1970). Despite the lack of research, sev- eral observers have suggested functions for friendship. Among these are: l 2 l) socialization (Weinberg, 1970); 2) personality stability (Weinberg, 1970); 3) therapeutic experiences (Maslow, 195A; Schofield, 196A); u) self-definition (Albert 8 Brigante, 1962); and 5) economic assistance (Cohen, 1961). To the extent that these factors are important or neces- sary to individuals, their presence would lead one to believe that close friendship is a significant class of social relations. Further, much of the significance of close friendship rests on the perception of the re- lationship as important by the participants themselves. Close friendship represents a distinct class of social relations. It can be distinguished from: 1) non-friendship; and 2) other levels of friendship. Friendship can be distinguished from non-friendship in several areas. The following paragraphs suggest five areas of distinction between the two types of relationships. First, positive affective orientations among participants are nec- essary for the existence of friendship, but not necessary to many other classes of social relations (Williams, 1959). Second, friendship is a voluntary relationship. One voluntarily enters in friendship relations. Similarily one can, painful as it may be, leave or dissolve a friendship--without the intervention of a third party and without any formal change in status (Suttles, 1970). This factor serves to distinguish friendship from marital relations. The latter typically cannot be dissolved without the intervention of a third party. Further, the dissolution of a marriage involves a formal change in status. Third, friendship represents an exclusive and private relationship (Suttles, 1970). It is not tied to social convention—~participants are 3 free to negotiate a personal norm set within such relationships. It is a truly interpersonal relationship in the sense that individuals relate to each other in terms of knowledge or information about the other as a unique individual (Miller 8 Steinberg, 1975). It is exclusive in that participants are committed to maintaining their unique relations or norm set (Suttles, 1970). Within the possible exception of marriage, no other social relationship involves such intense personal negotiation. Fourth, friendship engenders a high degree of equality between par— ticipants (Naegele, 1958; Cohen, 1961; Suttles, 1970). While distinct status differences may result from interaction in friendship over time, the participants initiate the relationship as equals. Not only are friends expected to treat each other as equals, but so too are the friends of friends. Friendship thus exerts a leveling influence not found in most other social relations. Marriage, for example, makes in-laws into kin, but not into equals (Suttles, 1970). Most other social relationships do not appear to depend upon or assume the degree of initial equality found in friendships. Finally, friendship implies an equality of information control not found to as great an extent in other relations. That is, regardless of the particular level of disclosure involved, most persons are likely to engage in reciprocal information handling in friendship. Trust, intimacy, and self-disclosure (factors traditionally associated with friendship) are likely to be reciprocal in friendship to an extent not found in other so- cial relationships (Simmel, 1950; Naegele, 1958; Williams, 1959; Suttles, 1970; Weinberg, 1970). Most of these distinctions between friendship and non—friendship are distinctions of degree rather than of kind. Taken in concert, however, these factors delineate friendship as a unique class of social relations. u Friendship itself, however, does not represent a monolithic set of social relationships. Naegele (1958) interviewed high school students and reported that several levels of friendship were perceived by respondents. Students distinguished levels of friendship primarily on the basis of the amount and breadth of self-disclosure involved. In order of increasing disclosure were the following categories: 1) acquaintances; 2) friends; and 3) close friends including one's best friend. In Naegele's data, then, close friendship was distinguished from other levels of friendship on the basis of the amount and breadth of self—disclosing communication. Kurth (1970) offers a more comprehensive explication of the distinc- tion between close friendship and other forms of friendship. Kurth distin— guishes between "friendship" and "friendly relations." The conceptualiza- tion of "friendship" is equivalent to what is classified as "close friend- ship" in the present work. Friendship is distinguished in the following paragraphs from friendly relations in six areas. First, while both are voluntary in nature, friendly relations are more dependent on the convenience of maintaining the relationship than is friendship. Friendly relations are usually severed when it becomes difficult for participants to maintain the relationship with a minimum of effort. Crudely placed within an exchange theoretic format, the argu- ment might be phrased as follows. There are limited rewards to be derived from friendly relations. Thus, when inconvenience creates increments in the cost of maintaining the relationship, it is likely to be dissolved. This is not so true of friendships. This probably reflects the higher value placed on friendships by the participants or the greater social sanctions associated with dissolving a relationship with someone who is perceived by others as a close friend. Second, a friendly relation lacks the sense of uniqueness found in a close friendship. To a much greater extent than friendship relations, friendly relations are perceived by participants as interchangeable. Each friendship, however, is perceived as a unique relationship among the par- ticipants. This may reflect the fact that there are likely to be higher levels of self-disclosure in a close friendship than in friendly relations. Third, while friendships are characterized by relatively high levels of reciprocal self-disclosure, important factors inhibit high levels of intimacy in friendly relations. Kurth suggests two such factors: 1) friendly relations frequently take place in situations which are not conducive to intimate revelations-—such as one's place of work; and 2) . . . friendly relation networks tend to inhibit reve— lation of intimate information, for none of the rela- tionships lends itself to intimacy more than any other and the revelation of information to one individual in the network might lead to its disclosure to a number of individuals (p. 1&0). Presumably, this sort of diffusion of disclosure tends to reduce the value of the disclosure and is thus devalued. Further, this implies that dis— closure in friendship can be expected to remain confidential—~a claim one cannot apparently make in a friendly relationship. While Kurth's rationale as to why disclosure is limited in friendly relations is not as clear or as defensible as one might wish, the central point is that close friendship is likely to involve higher levels of disclosure than non—close friendship (friendly relations). Fourth, obligations are generally more limited in friendly relations than in friendship. Kurth observes that: "the higher levels of obliga— tion and stronger positive sentiments are causes as well as consequences of the considerable personal involvement in friendship" (p. lul). Fifth, while strong positive sentiments are essential to close friend- ship, they are not so necessary to the maintenance of friendly relations. As Kurth asserts: ". . . we maintain friendly relations with those we do not have strong feeling for and perhaps even dislike somewhat" (p. 142). Finally, while friendly relations do not assume future interaction, such an assumption on the part of the participants is essential to the nature of interaction in close friendship. Kurth explains this notion: In a friendship individuals can draw on past credits and also trade in futures without disrupting the sense of balanced exchange. Thus, in an enduring relation— ship such as friendship, past experiences, and possi— bilities for the future as well as the current situa- tion affect the exchange in an encounter. On the other hand, friendly relations emphasize parity in encounters. When individuals establish a friendly relation, they are oriented to the present situation with the other, rather than to the past or future. Individuals in a friendly relation are generally not committed to extensive fu- ture relations. They try to avoid trading in futures because it commits them in the future to the develop- ment of a different type of relationship (e.g., a friendship) (p. 163). Taken as a whole, these distinctions between friendship (close) and friendly relations (non-close friendship) are primarily distinctions in degree rather than in kind. However, Kurth does suggest that: 1) levels of self-disclosure; and 2) the participants' orientations toward exchanges will be markedly different in the two types of relationships. While the logical consistency of the arguments is not always perfect, the distinctions discussed above do suggest that close friendship is a distinct and unique class of social relations. It differs in kind and in degree from non-friendship relations. It differs in degree and, to some extent, in kind from other classes of friendship (i.e., friendly relations). The distinctions between friendship and non-friendship and 7 between close friendship and non—close friendship have been summarized in Tables 1 and 2. Taking these considerations as a set, the following con— stitutive definition is offered for close friendship: Close friendship is that voluntary dyadic relation— ship characterized by: 1) high levels of mutual disclosure and trust; 2) strong positive affect; and 3) the unilateral ability of either member to terminate the relationship; and which is perceived by the participants as: a) unique; b) initially equal; 0) extended over time; and d) involving extensive and generalized obligations. The general thrust of this definition appears to be consistent with those factors identified by respondents in Naegele's (1958) study. Communication Networks From the mass of individuals in our social milieu, we select a set with which we maintain friendly relations and from that set we select a few with whom close friendship are formed (Chambliss, 1965). The forma- tion and functioning of close friendship implies active channels of com— munication (Festinger, Schachter 8 Back, 1950). Among a set of close friends there will be many possible channels of communication linking individuals. The frequency with which these potential channels are uti— lized will determine the structure of a communication network among a set of close friends. The structure of a communication network is expressed as the pattern of information flow among the individuals designated as members of that system (Danowski 8 Farace, 1974; Richards, 1974a). For example, assume that we have four individuals (A, B, C, D) comprising a communication net— work. By asking each person how frequently they communicate with the other three, we can discover the pattern of communication. By displaying the responses of all individuals, it is possible to portray the structure of the network itself. Consider the following hypothetical network: Table 1. Summary of Differences Between Friendship and Non-Friendship. Non-Friendship Friendship 1. Positive Affective Orientation 1. Positive Affective Orientation Not a Necessary Condition is a Necessary Condition 2. Formation and Dissolution Need 2. Formation and Dissolution are Not Be Voluntary in Nature Voluntary in Nature 3. Need Not Involve Relationship 3. Characterized by the Development or Individual Specific Mean— of Relationship and Individual ings and Norms Specific Meanings and Norms 4. Need Not Involve Initial 4. Characterized by Initial Equal- Equality Among Participants ity Among Participants and and Peers Peers 5. Need Not Involve Equality or 5. Characterized by Reciprocity Reciprocity of Information of Information Exchange Flow Table 2. Summary of Differences Between Close Friendship and Non-Close Friendship. Non-Close Friendship Close Friendship 1. More Dependent on Convenience 1. Less Dependent on Convenience for Maintenance for Maintenance 2. Not Perceived by Participants 2. Perceived by Participants as as a Unique Relationship a Unique Relationship 3. Less Intimate or Self-Dis- 3. More Intimate or Self-Disclosing closing Communication Communication 4. Limited or Bounded Obligations 4. Extensive Mutual Obligations 5. Less Dependent on Strong Posi- 5. More Dependent on Strong Posi- tive Affective Orientations tive Affective Orientations 6. Future Interaction Not Neces- 6. Future Interaction Implicitly sarily Assumed in Exchange Relations Assumed in Exchange Relations AH.IIIIII1)I3 C4l---i> Person A is linked to persons B and D who, in turn, are linked to each other. Person C is linked by communication only to person D. This pro— cedure allows us to view the structure of the communication network. While there are a number of methods by which one can describe a com- munication network, two of the most basic characteristics of communication networks are their size and integration.* These basic parameters are also the basis for more advanced measures of network characteristics (Richards, 1974c). The size and degree of integration of communication networks among close friends will constitute the dependent variables of primary concern in the present research. A closer examination of these two variables seems warranted. Network Size. Network size is the number of nodes in the communica— tion network. What constitutes a node may vary depending on one's parti- cular research interest. In this case, a node will be defined as an in- dividual who has been designated as a close friend by the respondent. The respondent is also counted as a node. The concern here will be with SEE? centric communication networks. That is, we are concerned with the struc- ture of the flow of communication among the close friends of the respondent. We are not interested in relationships among persons not designated as close friends by the respondent. Such networks are generated by asking the re- spondent to generate a list of his or her close friends. *For a more complete discussion of network variables and their mea— surement, see Richards (1974a, 1974b, 1974c). 10 In the study of friendship communication networks, size is an impor— tant variable for three reasons. First, the larger the network, the more persons one would presumably have to draw upon for emetional, economic, and other assistance (Rangell, 1963; Schofield, 1964). Second, the larger the communication network, the more persons one would have available as sources of information. Third, as we shall see at a later juncture, net— work size can be hypothesized as a major determinant of network integration. Network Integration. Network integration is a measure of the degree of linkage between individuals comprising a communication network. A link between persons may be conceptualized as an indicant of the existence of a relationship (Richards, 1974a). If persons A and B do not communicate, then no linkage exists. If persons B and D do communicate with each other, a linkage may be said to exist. The more frequently B and D communicate with each other, the stronger the linkage is. The strength of a link be— tween any two individuals, then, is conceptualized and Operationalized as the frequency with which they communicate. The more frequent the communi- cation, the stronger the linkage (Richards, 1974a). For a group of individuals, there will be many possible linkages. The total number of possible direct linkages for a given communication network may be derived from the following equation (Berlo, §t_al:, 1972; Richards, 1974c): P = __...___..N (II-l) (l) 2 Where: P = Total Possible Number of Direct Links of a Given Strength N = Number of Nodes (Size) The right side of the equation is divided by two because a link from per- son A to B is assumed to be the same as one from B to A. That is, com- munication is assumed to be reciprocal. 11 In the case where no communication occurs between persons, the strength of the linkage may be said to be zero. On the other hand, when individuals communicate at some arbitrarily set upper frequency, the strength of the linkage may be designated as one. For any given linkage, then, the fre- quency of communication will determine a strength ranging from zero to one. In equation (1) above, P may be viewed as the total number of pos- sible linkages among N persons where each linkage is assumed to have a value of one (maximal strength). This equation thus yields the total number of possible linkages at the highest possible strength for a net— work composed of N persons. The integration of the network is derived by computing a ratio of the total possible maximal strength linkages to the sum of observed strength values for all possible linkages: “stair? (2’ Index of Integration Sum of Observed Strength Values for All Linkages Maximal Link Strength Number of Nodes (Size) Where: Z’Ut‘H—I II II II II The Index of Integration accounts for both the number of individuals in the communication network and the frequency with which they communicate. The index will range from a low extreme value of zero, when all possible linkages have a strength of zero, to a high extreme value of one, when every node (individual) communicates with every other node at some maxi— mal frequency. This will be the case regardless of the number of nodes in the network since the value of the index (I) is expressed in terms of a ratio between parameters N and L. The Index of Integration presented here represents an extension of previous work by Farace and Monge, as reported in Berlo, §t_al:, (1972) 12 and Richards (1974c). These conceptualizations treated integration in an all or nothing sense--either a link was present or it was not. The con- ceptualization underlying equation (2) allows the investigator to account for the strength of linkages in deriving the index. Measurement of link strength is no longer limited to the nominal level. The significance of connectivity as a research variable in the study of communication networks among close friends rests on an appreciation of the significance and dynamics of small informal social groups. Friendship net- works have often been either explicitly (Klein, 1956; Hare, 1962; Cartwright 8 Zander, 1968b) or implicitly (Phillips, 1966; Applbaum, g£_al,, 1974) considered as small groups by small group theorists. The level of inte— gration, however, will affect the extent to which such a View is valid. The reasoning behind this assertion can be derived by examining the nature of small groups in general and the nature of group cohesion in particular. While a variety of conceptualization of small groups have been ad— vanced, most of them are in agreement at a general level. Bales (1950) offers the following general definition: A small group is defined as any number of persons engaged in interaction with each other in a single face-to-face meeting or a series of meetings, in which each member receives some impression or per- ception of each other member distinct enough so that he can, either at the time or in later ques- tioning, give some reaction to each of the others as an individual person . . . . (p. 33). In defining the term, Sherif and Sherif (1953) stress the characteristics of interdependent role relationships and a "set of values or norms of its own" as central components of small group interaction. Obviously, both of these views of "group" presuppose the flow of communication among mem— bers. Festinger, Schachter and Back (1950) point out: 13 Small social groups occupy a strategic position as determiners of the behavior and attitudes of their members. . . . Face-to—face communication among members of a social group would be a method through which much of the development of these attitudes and behavior would occur (p. 3). Unless persons are relatively interconnected through communication, how- ever, it would appear doubtful that we would be warranted in calling them a group. The extent to which group norms or values, impression of other members, interdependent roles, and the extent to which members' attitudes and behavior are influenced would be significantly diminished in the case where persons were not connected through a communication network. Thus, the degree of integration in the network would emerge as an important de- terminant of the extent to which close friendship network could validly be considered as "groups." This argument becomes stronger if we examine the nature of group co— hesion. This variable has come to play an important role in theories of group functioning. In his review of the literature on group cohesion, Cartwright (1968) relates group cohesion to levels of: 1) member satis- faction; 2) maintenance of membership; 3) ability of the group to influ- ence its members; 4) feelings of security in terms of anxiety reduction and an enhancement of self-esteem among group members; and 5) the degree of participation of members. However, unless members are high intercon- nected through a communication network, cohesion as the forces drawing and attracting persons to the group is likely to remain at very low levels. Under conditions of low integration, members would be less likely to: 1) perceive the aggregate of individuals as a unified whole, i.e., "a group"; 2) be exposed to other members directly; or 3) either receive or accept information from other persons. Under such conditions, it is extremely unlikely that any great amount of group cohesion will develop. 14 In sum, the level of network integration will be an important deter— minant of both the extent to which close friendship communication networks can be considered as small groups and the extent to which an important small group variable (cohesion) will influence the attitudes and behav— iors of participants. Study of network characteristics, then, is neces- sary to determine the extent to which the literature of small group re- search can be legitimately applied to close friendship networks. The primary dependent variables of interest in the present research are, then, network size and network integration. Network size is defined as the number of persons designated as members of the communication net- work. Integration refers to the numbers and strength of linkages among persons composing the network. The present research is concerned with networks among those individuals designated as "close friends" by the sub- ject. We now turn our attention to those variables which are hypothesized to be determinants of the size and integration of communication networks among close friends. Hypothesized Determinants of Network Characteristics In the following discussion a set of theoretically based variables will be presented. Their hypothesized relationship to network character— istics (size and integration) will be presented on the basis of theoreti- cal rationale and/or results of previous research. While the hypothesized determinants of network size and connectivity will be presented separately, the overall goal will be to develop a model descriptive of the entire set of relationships. Determinants of Network Size. Network size was conceptualized as the number of individuals designated by the subject (including the subject him- self or herself) as close friends. At a broad theoretic level we can 15 hypothesize that the size of such a network will be a function of: 1) one's desire to participate in such relationships; 2) one's ability to form and maintain such relationships; and, 3) one's Opportunities to en- gage in such relationships. This typology is believed to be exhaustive. A closer examination of each factor is warranted. As the earlier discussion of close friendship indicated, these rela- tionships tend to be high risk and high cost in nature. Large amounts of time and energy are expended in their maintenance (Rake, 1970; Suttles, 1970; Kurth, 1970). The fact that such relationships are voluntary clearly implies that one intentionally enters into them. Assuming this is the case, it would appear that one would not form or maintain such relationships un— less they held a positive attitude toward them. We shall treat this atti— tude as the level of desire the subject has for close friendship relations. This attitude is not a generalized one. One associates with other persons besides close friends. In fact, Kurth (1970) persuasively argues that under many circumstances simple ”friendly" relations would be prefer- able. Thus, a generalized "need for affiliation," level of "alienation" or degree of "sociability" would not appear to clearly explain the subject's attitude toward close friendships. One might, for example, have a very high "need for affiliation" but satisfy it through a network of acquaintances and casual friends. The desire to participate in close friendship relations would be a desire based on the unique qualities of that relationship which were advanced in the definition offered earlier. Among these would be the desire for a relationship or relationships involving: 1) a relatively in- tense positive affective orientation; 2) reciprocal disclosure and trust; 3) initial equality between participants; and 4) extensive and generalized obligations. 16 The second component of participation in close friendship relations is hypothesized to be one's abilities to form and maintain such relations. This ability will depend on the sorts of communication skills that one can bring to bear on the development and maintenance of close friendships. We would expect, then, that the more highly skilled the individual is in terms of interpersonal communication skills, the more easily and frequently he or she will be able to form close friendships. Thus, one's level of interper- sonal communication skills is hypothesized as an antecedent condition to network size. The final component or antecedent condition of network size is hypo- thesized to be the level of opportunity for participation. One may have the necessary desire and skills to participate in close friendship net- works, but unless one also has the opportunity to do so, the participa- tion would be expected to be minimal. The variables discussed below are all hypothesized as indicants of opportunity. We would expect that persons of high socioeconomic status would have more opportunities to participate in close friendship relations. Higher SES persons have more resources than lower SES persons by definition. An inverse relationship exists between social class and percentage of income spent on food, shelter, and clothing (Warner 8 Lunt, 1941). Hence, lower SES individuals would be less able to afford: 1) facilities for receiving guests in the home; or 2) extensive entertaining outside the home (Shuval, 1956). Additionally, such individuals are more likely to be physically fatigued from their work (Shaval, 1956). As we descend the socioeconomic ladder, then, we would expect individuals to have less and less opportunity to participate in close friendship communication networks. Socioeconomic status, as an indicant of opportunity would be expected to hold a positive relationship with the size of the communication network. 17 Previous research reports a consistently positive relationship between net— work size and SES (Lynd 8 Lynd, 1929; Shuval, 1956; Bell 8 Boat, 1957; Williams, 1958; Babchuk, 1965; Simon, Crotts 8 Mahan, 1970; Booth, 1972). In his review of this literature, Teele (1965) concluded that "there seems to be a direct relationship between having or seeing friends and social status." Several other variables may be considered as factors underlying Oppor— tunity. Among these are: l) membership in voluntary associations; and 2) the level of residential mobility. Both of these variables function to bring the individual into contact with greater numbers of persons. The greater the number of persons contacted, the more Opportunities one might have for the selection of close friends. This, in turn, may lead to the actual selection of a greater number of close friends. Thus, we would hypothesize a positive relationship between levels of membership in volun- tary associations and rates of residential mobility (as indicants of the opportunity variable) and the size of the communication network. Membership in voluntary organizations has been found to vary posi— tively with the number of close friends one has (Williams, 1958; Meadow, 1965) and the rates of interaction with those close friends (Axelrod, 1956). The relationship between residential mobility and network size has been the subject of a great deal of speculation but relatively little em— pirical research. Toffler (1970) asserts that under conditions of high mobility individuals will become more adept at forming close friendships in shorter periods of time. Presumably, this would result in a greater network size, although Toffler goes on to suggest that these relationships will not be very durable over time. Packard (1972), on the other hand, 18 takes the position that high mobility rates function to cut the individual Off from the community. Supposedly, this would result in a negative rela- tionship between the level of residential mobility and network size. In one Of the few quantitative studies in the area, Tomeh (1969) found that residential mobility was positively associated with participation in for- mal associations—-which as we noted above has been positively related to network size in other research. The relationship between network size and residential mobility is not resolved, but merits further examination-- especially in terms Of the theoretical perspective advanced here. Since one has only a finite amount Of time for participation in a communication network among close friends, we would hypothesize that any activity which commits the individual to communication with persons other than close friends would be negatively associated with network size. The formation and maintenance Of a series of close friendships requires time and effort. If this time and effort are directed elsewhere, we would ex- pect that there would be fewer of these relationships. High allocations of time to activities such as: l) spending time with non-friends; 2) spending time with non-close friends; 3) spending time with mass media sources; or 4) spending time alone, would be expected to reduce the op- portunities one has for the formation and maintenance Of close friend- ship relations. Thus, we would hypothesize a negative relationship be- tween these time allocation variables and network size. Under the general theoretic category Of Opportunity for participation, we have discussed seven variables: 1) SES; 2) levels of membership in voluntary associations; 3) rates of residential mobility; 4) the amount Of time spent with non-friends; 5) the amount of time spent with non- close friends; 6) the amount of time spent with mass media sources; and l9 7) the amount of time spent alone. All of these variables have been con— ceptualized as underlying the common factor of opportunity for participa- tion. On this basis, we would expect that these variables would be highly interrelated. We have already noted Tomeh's (1969) finding of a positive relationship between residential mobility and membership in voluntary asso- ciations. Further, there is a strong, positive relationship between social status and membership in voluntary associations (Dodson, 1951; Axelrod, 1956; Williams, 1958; Teele, 1965). In their review of the literature on this relationship Hodge and Treiman (1968) conclude: The positive association between membership in voluntary organizations and socioeconomic status is one of the best documented relationships in the sociological literature (p. 722). These findings suggest that these variables are not independent. The posi- tion taken here is that they are all indicants of the underlying dimension of opportunity. Obviously, analysis of the data should address itself di— rectly to this question. At a broad level, we have conceptualized desire, ability, and oppor- tunity as antecedent conditions of network size. We have examined the relevant literature with regard to each of these theoretic variables. Determinants of Network Integration. Network integration refers to the degree of linkage between individuals in a communication network. The conceptualization and measurement of integration have been discussed in a previous section. At this juncture, hypothesized determinants of inte- gration will be examined. These are: 1) network size; 2) perceived sim- ilarity; 3) propinquity or perceived effort; and 4) residential mobility. It is hypothesized that network size will be negatively associated with the degree of network integration. We would expect that as network size increases, it would become more difficult for participants to maintain 20 active communication with each other. Thus, the larger the network, the less the degree Of integration. Indirect support for this hypothesis can be found in the small group literature. Generally, it has been found that the larger the group, the less frequently any given individual participates in the communication activities of the group (Kelley 8 Thibaut, 1969). More direct support for this hypothesis comes from a study of communication net— work within a large financial institution. Danowski (1974) found that a strong negative relationship existed between network size and network integration. One Of the most consistent and best documented relationships in social science is that between liking or friendship choice and perceived similar— ity (Newcomb, 1961; Lott 8 Lott, 1965; Aronson, 1969; Byrne, 1969; Berscheid 8 Walster, 1969). We would hypothesize that: the more similar members of a communication network perceive themselves to be, the more integrated will be that network. Research on liking (interpersonal attraction) and friendship choice in terms of similarity has generally focused on: 1) attitudinal vs. per- sonality similarity; and 2) actual vs. perceived similarity. A brief re- view Of this literature will serve to explicate the hypothesis advanced above. The theoretic underpinning most Often articulated for the relation- ship between similarity (both attitudinal and personality) and liking or friendship choice is that of exchange theory (Berscheid 8 Walster, 1969; Aronson, 1969). Similarity with another person is hypothesized to be re- warding in terms Of an enhanced ability to predict his or her behavior (Kurth, 1970) and social validation for Our views or qualities (Berscheid 8 Walster, 1969). The hypothesis can also be derived from theories of 21 cognitive consistency. Berscheid and Walster (1969) explicate the relation— ship in terms of Heider's balance theory: . . . Heider proposed that people strive to make their sentiment relationships harmonious with their perception Of the unit relationships ex— istent between objects. According to Heider, separate entities which are similar tend to be perceived as belonging together (have a unit relationship). According to Heider's theory, then, positive unit formation (e.g., perceived similarity) should induce a harmonious senti- ment relationship (e.g., liking). This process, of course, should also Operate in reverse: lik- ing for another should lead to the perception that a harmonious unit relationship exists (e.g., that the liked other is similar to oneself) (p. 70). Employing a variety of experimental and non-experimental designs, in- vestigators have repeatedly found support for a positive relationship between actual attitudinal similarity and liking or friendship choice (Richardson, 1940; Precker, 1952; Byrne, 1961; Newcomb, 1961; Byrne 8 Nelson, 1965; Levinger 8 Breedlove, 1966; LaGaipa 8 Werner, 1971; Jackson 8 Mascaro, 1971). Byrne and Nelson (1965) found the relationship between the pro- portion of similar attitudes and attraction to be positive and linear. Extensive evidence has also been gathered indicating that liking or friendship choice leads to perceived similarity (Newcomb, 1961; Byrne 8 Blaylock, 1963; Nowak, 1963; Levinger 8 Breedlove, 1966; Berscheid 8 Walster, 1969). The bulk of this research has examined either friend— ship Or marital relations. Research has also indicated that perceived attitudinal similarity tends to be greater than actual attitudinal sim- ilarity (Byrne 8 Blaylock, 1963; Levinger 8 Breedlove, 1966). The relationship between actual similarity in terms of personality traits and liking or friendship choice has also been the subject of ex- tensive research. Typically, these studies compare friends' or spouses' 22 profiles on some Objective personality inventory.* Several studies have found a positive relationship between personality traits and profiles of persons exhibiting high attraction toward each other (Bonney, 1942; Reader 8 English, 1947; Izard, 1960; Banta 8 Hetherington, 1963; Izard, 1963; Poe 8 Mills, 1972). In her review Of over 50 studies Of personality and atti- tudinal similarity among friends and spouses, Richardson (1939) concludes that: Throughout all the traits and the ranges of ages the correlations between the paired scores of friends or marriage partners have been positive with very few exceptions (pp. 116-117).** Other studies with similar designs and subject populations, however, have produced results which indicate no relationship between actual personality similarity and liking or friendship choice (Hoffman, 1958; Commins 8 Stefic, 1960; Day, 1961; Mehlman, 1962; Coats 8 Mazur, 1969). In general, positive correlations between these personality variables and attraction have not been found with the regularity with which positive correlations between attitudinal similarity and liking have been found. Further, personality similarity and liking tend to have lower correlations (when positive re— lations are found) than attitudinal similarity and liking. These results have prompted Berscheid and Walster (1969) to speculate that to the extent personality similarity is a factor in attraction, "it is perhaps a less important one than attitudinal similarity." Perceived personality similarity, as Opposed to actual similarity, has tended to receive more consistent confirmation as an antecedent to *The most frequently used profile has been the Edward's Personal Preference Schedule. **The author does not present any significance levels for these correlations, however. 23 attraction or friendship choice. A variety of studies have found a posi- tive relationship between friendship choice or attraction and perceived personality similarity (Beier, Rossi 8 Garfield, 1961; Broxton, 1963; Secord 8 Backman, 1964; Miller, et al., 1966). Miller, et a1. (1966) argue that this relationship represents an overgeneralization on the subject's part. In sum, the literature gives strong support for a positive, linear relationship between actual or perceived attitudinal similarity and inter- personal attraction or friendship choice. Perceived personality similar— ity is also positively related to attraction or friendship choice, but actual personality similarity is not consistently related to liking. Re- latively little research, however, has been directed toward isolating the direction of these relationships. That is, we are asking if the predom- inant path Of influence is from similarity to attraction or from attrac- tion to similarity. Evidence to support the relationship in both direc— tions has been reported. Most investigators have treated the relation— ship as non-recursive (Lazarsfeld 8 Merton, 1954; Newcomb, 1961; Lott 8 Lott, 1965). Given that the degree Of liking is positively related to the frequency of communication (Festinger, Schachter 8 Back, 1950; Bovard, 1951; Bovard, 1956; Chambliss, 1965), we would hypothesize a positive, linear, non-recursive relationship between overall perceived similarity among participants and the degree of integration in the communication network. Substantial support has been found for the hypothesis that physical proximity and frequency Of interaction are positively related (Caplow 8 Forman, 1950; Festinger, Schachter 8 Back, 1950; Gullahorn, 1952; Maisonneuve, Palmade 8 Fourment, 1952; Willerman 8 Swanson, 1952; Kipnis, 24 1957; Riemer 8 McNamara, 1957; Deutsch 8 Collins, 1958; Loether, 1960; Menne 8 Sinnett, 1971). In a broad sense, the explanatory variable under- lying these findings can be conceptualized as "effort to communicate." The easier it is to communicate with someone, the more likely it is we will communicate with that person--a11 other things being equal. Since physical proximity implies that persons would require less effort to com- municate, we would expect proximal individuals to communicate more fre- quently than distal individuals. In general, we would expect that per— ceived effort of communicating with a given individual will be negatively related to the frequency of actual communication with that individual. Since frequency Of actual communication is the central component Of net- work integration, we would hypothesize that: the greater the level of perceived effort to communicate with other members, the less well inte— grated the network will be. In addition tO Offering an explanatory vehicle for the propinquity/ interaction findings, effort is a useful conceptualization from the opera- tional standpoint. If we use residential propinquity, we are immediately faced with the lack Of a stable referent. Individuals, for example, may live far apart, but share a common Office. In this case, residential pro— pinquity would be a less than adequate measure of functional or actual propinquity. On the other hand, if we use proximity in terms of place Of work, we have the same problem if we find that some individuals who live close together, but who are widely separated in terms of their work setting. By using level of effort, we avoid these difficulties. The final hypothesized antecedent of network integration to be dis— cussed in the present research is residential mobility. Again, relatively little previous research can be brought to bear on this relationship. 25 However, if we assume that individuals do make close friends as they trav— el about, then it would seem logical to assume that the more spatially mo- bile one is, the less integrated would be his or her communication network. Residential mobility will have both a direct and indirect influence on net— work integration. First, it would be less likely that one's close friends either know or communicate frequently with each other under conditions of high mobility. In this case, the level of residential mobility would be hypothesized to have a direct, negative influence on the level Of network integration. Second, as indicated above, as one's proximity to close friends decreases as a result of residential mobility, greater effort would be required to maintain communication at any given level. This increased effort should result in decreased frequencies of communication with one's close friends. Residential mobility and effort are assumed to be positively related in this case. Here, residential mobility would have an indirect and negative impact on integration through perceived effort. On this basis, it is hypothesized that: the higher the rate of residential mobility, the lower the degree Of network integration. In a broad sense, then, network integration is hypothesized to be a function of four variables. These are: 1) network size; 2) perceived similarity level; 3) perceived effort to communicate; and 4) the rate of residential mobility. Network size and perceived effort are hypoth— esized to be negatively related to integration. Perceived similarity and integration are hypothesized to be associated in a linear, positive, non-recursive fashion. Residential mobility is hypothesized to have a direct negative impact on integration and an indirect negative impact through perceived effort on integration. A_Causal Model 2£_Determinants 9f_Network Characteristics. The re- lationships hypothesized above may be viewed as comprising a system of 26 causal relationships. The path or causal model below (Figure 1) is an attempt to explicate and identify the nature Of the logical and empirical relationships within that system. Our concern in the model is not so much with individual bivariate relationships as with all relationships taken in concert as a system. Network size is hypothesized to be a function of one's desire, abil- ity and Opportunity to participate in close friendships. Opportunity is conceptualized as the underlying characteristic common to the following variables: 1) SES; 2) number Of memberships in voluntary associations; 3) residential mobility; 4) time spent alone; 5) time spent with mass media; 6) time spent with non—close friends; and 7) time spent with non— friends. Opportunity has the status Of an unmeasured variable. Network integration is hypothesized to be a function Of: 1) network size; 2) perceived similarity; 3) perceived effort; and 4) residential mobility. Residential mobility is hypothesized to have a direct effect on integration as well as an indirect effect mediated by perceived ef- fort. The relationship between network integration and perceived simi— larity is hypothesized as non-recursive. All other relationships in the model are hypothesized as recursive. 27 .mpcmceahmpom QHOLB com mowpwwpopomsmno xnozpoz mo Hocoz Homsmo OONHmmzpoamm .H mesmea .oanmflnm> condmmoecs am we mpwaspeooao .Ooupwao coon o>mn moanmflem> msocmmoxo maoam cam wamsoemop macaw manumaoppoo .muwemao pom .manop Hmdemon wpwcmwmoo mempuoa HHOEm ”ovoz a Szfifiéazhfieé 2 1580-205sz #I / oI'fisz mmAI ' nIO emonfim OI wquHmozoI I/ u AseHzaemommov >nlvona .emEhowmcmspcs .amcwmwso mew pom mam mowpmflpmpm m>wwewpommw .mommo HHm CH Hmawwwso one mo mcowumEpommcmmp owezpfismwoa ones :H: spa: umpawsomASm moaansm> V I 94 Ho. mo. .mmanmwsm> .oHnmwpm> some pom mm H 2 V l CL =tt: .m H oH. «om. «oo.-«mo. eHj. oo.-eoo. «mo. oo. «so. No.- :H.- mo.- AoH.H o om.o spHcopaoooo s H Ho. oH.-«oo. NH. oH.- Ho.- oo.- HH.- mo. so. sow. som.- Hoo.s o 5H.oH Hoongc-coz\oeHe on H :H.- oo.- sH.- om.- oo. oo. mo.- mH. oo. oo. oH.- Hoo.o V oo.o HsHHHHooz on H oH.- oH.- mo. oH. som.- mo.-smm.- :H.- oH. so.- Hos.mHo oo.mo mc0H<\oeHo HHx H oH. Ho. mo. sH. mo.- oH. mo.- NH. oo.- HoH.HHo Ho.oH HmmOHo-coz\meHe on H som.- oo.- oo. oH.- oH. mo.- oH.- so. Hoo.oHo so.m: HmHooz mmmz\meHe ox H Ho. mH. Ho.- mo. mH. RH.- oo.- Hom.oHo om.mo Hmmm ox H NH. HH.- NH. mH.- oH. mo. HHN. o om.H H.oowm< shopaoHo> 5x H ego. 3H. Hm.- mo.- 5H. Hoo.oHo so.so mHHme cOHHmoHcoeeoo ox H oo. oH. HN.- mo.- Hon.» o oo.oo HoaHmoo ox H oo. oo.- oo.- Hmo.o o Ho.» ouHm xaospoz ox H moo.-eoo.- Amo.H o oo.: ppommm oo>Hoopoo ox H so.- Hoo.H o om.m squmHHeHm oo>Hooaom «x H Aoo. o oo. HaoHumpmoch xpozpoz Hx » me me HHx on ox ox ex ox ox ox ox ox Hx H.o.mo com: mmHAmem> pom moflpmwumum m>wpmwpomoo pom wooe< mcowpmamspoopoucH .m magma 51 .mmHannm> wooe< mCOMVMHmnmoo wwwHOIOLwN mo chmppmm may mawvmowuaH deco: .o opsmHo mvcmfinmucoz spa: pcmam mafia n max muHHHnoz Hmflucmewmmm mo Ho>mq n max mHHme covaowcaseoo u mx meoa< “comm mafia u Hax wwwmoa u mx mecmwpm wmoaoucoz spas ucmmm mafia u oax muwm xnozpuz u :x mmowsom waves mmmz Ava: pcomm mafia n ox unommm wm>flmonom u mx mmm u mx huwnmawEHm vm>Hoonom u m mcompmwoomm< >nmucsao> ca magnmnmnsoz u bx nowumpmuucH xnozpuz u x "when; Ho. .v. 9... von mo. w me \\\ mo.+ \IOHH mocmowmwcmwm x «mm.u \ .4 oax \ ma.+ m .tLv x \ ma.+ ithx oo.+ .33.: \ {vex NH.+ ax I tax 4 :H.+ a: mo.+ x m 52 a result, there may be no inherent reason for desire as such to be related to network size. The relationship between communication skills and network size was also found to be problematic. It was hypothesized that greater quantities of interpersonal skills would yield greater numbers of close friendships. It may be the case, however, that a certain level of communication skills is necessary to maintain any close friendships and that once this level is reached, further increments in skills do not yield further increments in network size. Here, the relationship between skills and size would be non-linear. This alternative hypothesis, while intuitively plausible, could not be tested with the present data set given the fact that: 1) all subjects were able to identify one or more close friends; and 2) there were no extremely low scores on the communication skills inventory. It should also be noted that desire and communication skills are significantly correlated with each other (r = .24, p'<.05). This result suggests that in addition to direct effects of X5 (desire) and X6 (com— munication skills) on X4 (network size), there are two indirect paths operating. The first is from X6 through X5 to X”. The second is from X5 through X6 to X”. As a result the relationships among these three variables have not been clearly specified by the present research. The number of memberships in voluntary associations (X7) and the socioeconomic background of the subject (X8) were hypothesized to be positively related to Opportunity (Y1) which in turn was hypothesized to be positively related to network size. One would speculate, then, that these two variables (X7, X8) would be positively related to network size. However, neither of the correlations was large enough to obtain statistical significance. The number of memberships in voluntary associa- tions was somewhat more strongly related to network size (r = .12) than 53 was SES (r = .03), but neither of the associations was strong. With regard to the relationship between SES and network size, a partial explanation for the failure to support the hypothesis might rest in the nature of the sample. Most subjects had a relatively high SBS (M_= 82.28) and for the entire sam— ple there was a relatively small amount of variance (§D_= 14.26). This distribution may have precluded an adequate test of the hypothesized re- lationship. The nature of the sample can also be examined for an alter- native hypothesis with regard to the hypothesized relationship between network size and memberships in voluntary associations. In the earlier discussion of this relationship it was suggested that memberships in vol— untary associations functioned to bring the individual into contact with groups of persons from which some subset was selected for the close friend- ship relationship. However, on a university campus normal classroom meet- ings and living arrangements may serve the same function. Thus, it is plausible that other mechanisms which directly affect more persons are operating in the university community. In such a case, memberships in voluntary associations might not play as important a role as they might in other situations. The time spent with mass media sources (X9), with non-close friends (X10) and with non-friends (X13) were hypothesized to be negatively associated with network size through opportunity. The data did not support these hypoth- eses. None of the correlations were in the hypothesized direction and none reached statistical significance. The rationale behind these hypotheses was that the more time individuals spent in other pursuits, the less time they would have to spend with close friends. As a result, individuals with less time would probably be able to support fewer close friendships. Obviously, an alternative hypothesis is that time can be simultaneously with close 51+ friends, mass media, non-close friends, and non-friends. An additional rival hypothesis relates to the fact that since the various categories of time allocation used in the present study were not necessarily exhaustive, the individual might well have taken time from other, unmeasured activities to devote to the development and maintenance of close friendship relations. Thus, high allocations of time to the measured categories would not neces- sarily preclude high allocations of time to close friendships. The final variable with regard to the allocation of time was the amount of time spent alone. The relationship of this variable to network size was significant and in the hypothesized direction (r = -.22, p (.05). It is worth noting that this result does not fully negate the first alternative hypothesis advanced with respect to the other time allocation variables. Time spent alone obviously is time that cannot be spent with close friends. The other categories of time allocation employed in this study do not pre- clude simultaneous activity with close friends. However, it should be noted that time spent alone could be time simultaneously spent with mass media. Residential mobility (X12) was hypothesized to be positively related to opportunity (Y1) which in turn was hypothesized to be positively related to network size (Xu). Since opportunity was an unmeasured variable, it cannot be considered at this point in the discussion. However, we would expect the relationship between mobility and size to be positive. The obtained zero-order correlation was in the hypothesized direction (r = .13), but failed to reach statistical significance. Mobility was presumed to be related in a positive manner to network size by virtue of the belief that mobility would function to bring the individual into contact with greater numbers of others. A result of contact with greater numbers of others was believed to be greater numbers of close friendships. However, 55 another potential result of increasing levels of residential mobility might be a decreasing ability to maintain the close friendships left behind. If this is true, then the individual would be both gaining and loosing close friends as a result of moving. It does appear, however, that individuals are able to maintain close friendships over relatively great distances. When asked to estimate the distance between themselves and each of their close friends, subjects reported an overall mean distance of 462.28 miles. Determinants of Network Integration. Network integration was hypoth— esized to be a function of four variables: 1) the level of perceived simi- larity in the network (X2); 2) the level of perceived effort in the network (X3); 3) the level of residential mobility (X12); and 4) the size of the network. The zero-order correlation between perceived similarity and network integration was small (r = -.07). The interpretation of this result must begin with an appreciation of the nature of measurement. Both of these variables were estimated from the perspective of the subject. A more complete procedure would have been to obtain estimates from all members of the network. It might be the case that the subjects' perceptions of similarity were not as accurate as would have been the estimates of the network members directly involved in a given judgment. If so, there need be no necessary relationship between estimates of similarity and estimates of rates of communication. This may be an especially severe problem with a subjective judgment like similarity. The zero-order correlation between perceived effort and network inte- gration was significant and in the hypothesized direction (r = -.38, p <.Ol). To some extent the fact that this association reached statistical signifi— cance mitigates the assertion that the subjective nature of the judgments 56 being made might reduce the level of association. Surely, judgments of perceived effort are as subjective as those of perceived similarity. The zero-order correlation between residential mobility and network integration was in the hypothesized direction but failed to reach statis- tical significance (r = -.l9). The association nearly reaches an accept— able level of significance (p‘<.05) but falls short (p <.O9). There ap— pears to be a strong trend in the data. Residential mobility was also hypothesized to be positively related to perceived effort. This correlation proved to be quite small (r = .06). This might have been due to the fact that physical distance separating people has become less of a barrier to communication as a result of con— tinuing improvements in long—distance communication facilities (Packard, 1972). That is, the increasing separation which would seem to be implied by increasing levels of residential mobility need not necessary result in increasing difficulties in maintaining a given rate of communication. An additional alternative hypothesis is that residential mobility by itself need not result in great increments in the physical distance separating communicants and thus might not increase the amount of effort necessary to maintain a given rate of communication. The final hypothesized determinant of network integration was network size. The correlation between these two variables proved to be extremely small (r = -.03). This result was counter to previous findings in other settings--notably those of Danowski (1974). One potential explanation rests with the fact that neither of the variables has a great amount of variance. Another potential explanation might be that the university brings persons into such close proximity that it is relatively easy to communicate with other members of the network regardless of how many 57 other members there are. Of course, the rather large mean distance (462.28 miles) between the participant and each of his or her close friends reduces the plausibility of such a hypothesis. In any case, since previous research which has found a significant negative association between these two vari- ables employed non-student samples, a point of departure should be the care- ful examination of the distinctions between student and non—student samples. Multiple Regression Analysis The hypothesized model was divided into two sets of regression equa- tions. One relates the exogenous variables of desire (X5), communication skills (X6), and opportunity (Y1) to the dependent variable of network size (Xu). The second relates perceived similarity (X2), perceived efa fort (X3), residential mobility (X12), and network size (X4) to the de— pendent variable of network integration. Figure 3 graphically portrays the relationships among these variables derived from multiple regression procedures. Determinants of Network Size. Network size was hypothesized to be a function of three variables: 1) desire; 2) communication skills; and 3) opportunity. Since opportunity was an unmeasured variable in the present investigation, it was first necessary to obtain an estimate for it. The procedures employed to do this are outlined in Appendix VI. Multiple regression procedures relating the three hypothesized de- terminants of network size indicated that the major impact on size was opportunity. This was the only partial regression coefficient (beta weight) which reached statistical significance (beta = .36, p<:.01). The other regression coefficients were quite small and did not approach statistical significance. The multiple correlation was relatively large 58 .mmemHnm> semmz mcoe< mpcmwowmmmoo coflmmmnmwm mo csmppmm one mowmeHch Hope: .m mssmwm Amm u av .Umpvwso amen w>mn mcowu enamoo n mx . I a Imamnnousmpcfi nwmnp mam mssmp muwm xpospmz u :x HO v %% HMSUHWMQ .%HHQMHU 90m u®#OZ PQOMMM Uw>flmohmm H mx mo. v as mpHHmHHEHw pm>fimonmm u mx . mpwaflboz Hmfiucmpflmmm n max cowpmsmwucH xwozpmz u ax ”wocmonHcmwm waawxm coaumowcsssoo u ox hpwcsppoamo n a» "when: team.n mo.+ Afia: n xv I H «#mm.+ mba.+ s:w.+ 59 but failed to reach statistical significance (R = .35, p< .06). It can be said that the major determinant of network size in the present study was the level of opportunity individuals had to participate in such networks. Neither the level of desire for participation or the level of communica— tion skills of the subject seemed to be related to network size. A problematic factor with the findings with respect to these variables is the existence of relatively high zero-order correlations (see Table 6) among the independent variables. These intercorrelations imply that the relationship between the exogenous variables and network size represents some indeterminant combination of direct and indirect effects. Table 6. Intercorrelations Among Exogenous Variables.a Yl Opportunity 1 X6 Communication Skills .35** 1 X5 Desire .09 .24* 1 a N = 58 for each variable *p f .05 **pf .01 Determinants of Network Integration. As Figure 2 indicates, the only variable which was significantly associated with network integration was perceived effort (beta = —.38, p <.01). Despite the insignificant contri— butions of the remaining three variables (perceived similarity, network size, and residential mobility), the overall multiple correlation proved to be significant (R = .41, p <.05). The general pattern of results ob- tained from multiple regression analysis of these variables, however, can 60 probably be more parsimoniously explained by the simple association between perceived effort and network integration. The other variables do not make important contributions to the amount of variance explained. Some tenta— tive explanations for these results were advanced in the preceding discus— sion of zero-order relationships. A Path Analytic Evaluation of the Causal Model A more comprehensive analytic technique than those applied up to the present point is path analysis. For a model involving recursive relations among variables, path analysis represents an extension of conventional re- gression analysis (Duncan, 1971). It functions to cast regression analysis into a pattern of interpretation. Path analysis may be viewed as a tool for making explicit the rationale for and the interpretation of a set of regression equations (Duncan, 1971). In the recursive case, path analysis of a model typically entails a series of interlocking regression procedures (Kerlinger and Pedhazur, 1973). More complete discussions of the nature of path analysis can be found in Kerlinger and Pedhazur (1973) and in Van de Geer (1971). A comprehensive application of path analytic techniques to the present data set was not possible for several reasons. The primary reason was the unavailability of the necessary computer software. Standard regression analysis does not yield: 1) the correlations among the residual terms; 2) a solution for the non-recursive relationship hypothesized between network integration and perceived similarity; or 3) a unified set of procedures for dealing with unmeasured variables. As a result, the ap— plication of path analysis to be presented here is incomplete. Improvised procedures involving hand computation were applied in several instances, but the magnitude of the task precluded a complete solution of the model 61 by such procedures. The necessary procedures and computer software for the solution of the hypothesized model have been developed Joreskog and his associates (Joreskog, 1969, 1970a, 1970b, 1971; Werts, Joreskog and Linn, 1973). This software was not fully mounted on the Michigan State University computer system at the time of analysis. It must be stressed, then, that the path analytic procedures discussed below are incomplete and that conclusions based on that analysis are preliminary and tentative. Before attempting to evaluate the model as a whole, it is necessary to discuss its derivation in two specific areas: 1) the estimation of path coefficients linking Opportunity to its hypothesized underlying vari— ables; and 2) the estimation of the path coefficients in the non—recursive relationship between perceived similarity and network integration. Opportunity (Y1) was estimated as the linear combination of those variables hypothesized to underlie it (X7 - X13). The procedures by which this estimation was made have been outlined in Appendix VII. Once opportunity had been estimated, it was necessary to obtain estimates of the path coefficients linking opportunity to the hypothesized underlying variables. These estimations involved hand computation and have been presented in Appendix VII. In brief, the estimation of these path co- efficients involved multiplying the matrix of path coefficients (stan— dardized partial regression coefficients) obtained when the underlying variables were regressed on network size by the zero—order correlation matrix for the hypothesized underlying variables. This procedure yielded estimates of the path coefficients which accounted for the unmeasured variable (opportunity). Because of its non—recursive (reciprocal) nature, conventional re— gression techniques did not fully specify the relationship between per- ceived similarity (X2) and network integration (X1). There were actually 62 two path coefficients to be estimated. The first was the path from per- ceived similarity to network integration. The second was the path from integration to perceived similarity. The procedures employed for these estimations have been outlined in Appendix VIII. In both of the cases where hand computation and estimation procedures were applied, it became difficult to obtain precise estimations of the level of significance associated with each of the path coefficients, further re— stricting attempts to evaluate the model. The hypothesized model cast into a path analytic format is presented in Figure 4. Before examining its specifics, several general characteris— tics of the solution should be noted. First, most of the path coefficients fail to reach statistical significance. Because of the difficulties in estimation discussed above significance estimates were not obtained for several of the paths. Nonetheless, the absence of statistically signifi- cant path coefficients suggests that the model as constituted and specified was not well supported by the data. Second, the almost uniformly large value of the residuals (Range = .83 to .99) suggests that the hypothesized relationships do not account for a substantial amount of variance. Third, the fact that the three exogenous variables are significantly interrelated suggests that: 1) the effects of these variables on network size were not fully clarified by this analysis; and 2) the estimations of other paths which involved mathematical manipulation of these vari- ables were prone to error. Multiplication by exogenous variables was involved in the estimation of the non-recursive paths (See Appendix VIII). Three specific path coefficients merit special discussion. First, the significant path ( +.36, p <.05) in the hypothesized direction link— ing opportunity and network size is the only statistically significant 63 .pmshom owuhamc< cpmm ousw pmmo Homo: umufimwnpomhm .: osswwm .manmawm>m mmz Hm>wH cosmofimwcmfim mo wumeflumm 0s .c0flpmusano pawn he mms 832$ch 33 9:82 oo.+ lemozmHE-zoz\mz:.9 mpcmwowmmmoo npma may wo HH.+ W eonEHpmm $ch ”302 so .+ 1530-323on” . ma.+ I Ho. w use mm.+.lll!0 :H... V mm . + 158mm A! E. 4302? J :H.+ HeeHzoemooooo mm.+ «mm.+ em I mo.+ mm . + Ilvonh _.__.. PERSON YOU LIST. If you are married, please do not count your spouse as a close friend--even though he or she may be one. Please be complete, but do Not Feel As If You Must Fill In Every Blank. PLEASE PRINT. 1. Sex: male female. 2. Sex: male female 3. Sex: male female u. Sex: male female 5. Sex: male “female 6. Sex: male female 7. Sex: male female 8. Sex: male female- 9. Sex: male female If you need more space--it is provided on the next page. Be sure to list all persons who meet the definition. DO NOT LIST ANYONE NHO YOU DO NOT CONSIDER TO BE A CLOSE FRIEND ACCORDING TO THE DEFINITION ABOVE. 10. 11. 12. 13. 14. 15. 87 Sex: Sex: Sex: Sex: Sex: Sex: male male male male male male female female female female female female If you need more spaceo-please continue on the back of this page. indicate the sex of each person. 5.9.22 2.9.27? 1. WRITTEN YOUR NAME IN THE SPACE AT THE TOP OF PAGE 2? 2. COMPLETED ALL ITEMS ON PAGE TWO? 3. LISTED ALL PERSONS WHO MEET THE DEFINITION, BUT NONE WHO DO NOT? u. INDICATED THE SEX OF EACH PERSON LISTED? Please hand in this questionnaire when you are finished. THANK YOU FOR YOUR COOPERATION. Be sure to print the name of each person clearly and 1-1 APPENDIX II: WAVE #2 APPENDIX II: WAVE #2 I'D. ' MICHIGAN STATE UNIVERSITY Have # 2 College of Communication Arts Department of Communication Dear Participant: East Lansing, Michigan 48824 This is the second of four questionnaires concerning your communication in close friendships. Although there are a fairly large number of items, it is important carefully and answer it sincerely. that you consider each question If you have any questions about any of the items, please call me. Office Phone: Home Phone: 355-1862 355-0789 You should be able to contact me or leave a message for me at these numbers. Please do not call before 7:30 in the morning or after 10:30 at night. Remember that all information you confidential. give me will be kept strictly PLEASE RETURN THIS QUESTIONNAIRE AT THE NEXT MEETING OF THIS CLASS OR TO ME IN R00! 423 SOUTH KEDZIE HALL. . Thank you, ’4' ‘f h. I ("1 -. ’jv ' Mac-Parks ' V ' Principal Investigator 88 1. 89 HOW MANY CLUBS OR.ORGANIZATIONS DO YOU BELONG TO? LIST THEM. List all clubs or organizations which you belong to either on-campus or off-campus. Examples would be: Church clubs, activity clubs like chess clubs, sports clubs, service clubs like Circle K, Lions, sororities or fraternities, and professional organizations. LIST ALL CLUBS OR ORGANIZATIONS YOU BELONG TO: 10. 11. 12. 13. 14. 15. (If you need more space--please continue on the back of this page.) 90 YOUR FATHER'S OCCUPATION: (OR WAS, IF DEAD OR RETIRED) (SPECIFY THE KIND OF WORK HE IDES, NOT I'THERE HE WORKS). For example, "My father works as an assistant manager of a department store." IN COMPARISON WITH THE INCOME 0R.NEALTH OF FAMILIES IN YOUR COMMUNITY, DO YOU THINK.YOUR FAMILY IS: (Check one) 1. Considerably Above Average 2. Somewhat Above Average 3. Average 4. Somewhat Below Average 5. Considerably Below Average HOW MANY YEARS OF SCHOOLING DID YOUR FATHER AND MOTHER COMPLETE? (Check one for each) _ FATHER MOTHER less than 8 grades 8 grades 9 to 11 grades 12 grades graduated from high school some college graduated from college an advanced degree (Masters, Ph.D., or professional such as law or medicine) 91 ESTIMATE THE ANNUAL INCOME OF YOUR FAMILY-- s MY FATHER IS ENGAGED IN THE TYPE OF OCCUPATION CHECKED BELOW: Office Work (Cashier, clerk, secretary, bookkeeper, etc.) Owns, Rents, Manages a Farm Other Occupation (Be Specific) Professional (Doctor, lawyer, minister, teacher, etc.) Executive (Manages large business, industry, firm, etc.) Factory Worker (Laborer, janitor, farm hand, etc.) Salesman (Insurance, real estate, auto, store, etc.) Owns, Rents, Manages Small Business (Store, station, cafe, etc.) BELOW IS A LIST OF ACTIVITIES. YOUR JOB IS TO ESTIMATE HOW MUCH TIME (IN HOURS) YOU SPEND ON EACH ACTIVITY ON AN AVERAGE WEEKDAY AND ON AN AVERAGE WEEKEND DAY. Be sure that your list for each day does not exceed 24 hours. AVERAGE AVERAGE ACTIVITY - . . MEEKDAY . WEEKEND DAY A. Watching television-- hrs. 5 hrs. -- .._... ._.-__.....__.__._- __ ‘_ -_.-_., .-| __ T B. Reading books, magazines, ! newspapers, etc. -- hrs. hrs. , ‘ _.- ..._.._ ! ii 3 ' C. Listening to the Radio, Stereo—- hrs. 2 hrs ’ (List only the hours when you i were doing nothing except listening) i D. Talking with persons who are ‘ friends but who are not close : hrs. 1 hrs. friends-- . i E. Talking with persons who are A neither close friends or other ‘ hrs. hrs. types of friends:- w J F. Time spent alone-that is, time you were not actually with one 1 hrs. hrs. or more other persons. Include ; hours of sleep. 8. 92 BELOW IS THE LIST OF YOUR CLOSE FRIENDS THAT YOU PROVIDED BEFORE. ESTIMATE HOW MANY MILES EACH PERSON LIVES FROM YOU. IF A CLOSE FRIEND LIVES LESS THAN A MILE FROM YOU, USE A FRACTION TO ESTIMATE THE DISTANCE. 1. lives miles from me. 2. lives miles from me. 3. lives miles from me. 4. lives miles from me. 5. lives miles from me. 6. lives miles from me. 7. lives miles from me. 8. lives miles from me. 9. lives miles from me. 10. lives miles from me. 11. lives miles from me. 12. lives miles from me. 13. lives miles from me. 14. lives miles from me. 15. lives miles from me. 9. 93 BELOW IS A.LIST OF ITEMS ABOUT HOW YOU COMMUNICATE WITH OTHER PEOPLE. PLEASE ANSWER.ACCORDING TO THE WAY YOU FEEL AT THE PRESENT TIME. PLEASE BE AS FRANK AS POSSIBLE SINCE YOUR ANSWERS ARE CONFIDENTIAL. IF YOU CAN NOT BE SURE YOU CAN BE SURE A CHECK GIVE THE EXACT ANSWER TO A QUESTION, ANSWER THE BEST YOU CAN, BUT TO ANSWER EACH ONE. ANSWER EACH QUESTION IN ONE OF THREE WAYS. --- Answer "YES USUALLY" when the question can be answered as happening most of the time or usually. --- Answer "NO SELDOM" when the question can be answered as happening seldom or never. --- Answer "SOMETIMES” only when you definitely can not answer "yes" or "no". TO ANSWER ALL ITEMS. THERE ARE NO RIGHT 0R WRONG ANSWERS. PUT MARK (V) IN ONE OF THE SPACES. YES NO USUALLY SELDOM SOMETIMES 1. Do your words come out the way you would like them to in con- versation? 2. When you are asked a question that is not clear, do you ask the person to explain what he means? 3. When you are trying to explain something, do other persons have a tendency to put words in your mouth? 4. Do you merely assume the other person knows what you are trying to say without your explaining what you really mean? 5. When in a discussion, do you attempt to find out how you are coming across by asking for feedback? 6. Is it difficult for you to converse with other people? 7. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 9M YES USUALLY Do you find it very difficult to become interested in other people? Do you find it difficult to ex- press your ideas when they differ from those of persons around you? In conversation, do you try to put yourself in the other per- son's shoes? In conversation, do you have a tendency to do more talking than the other person? Are you aware of how your tone of voice may affect others? When you are angry, do you ad- mit it when asked by someone else? Is it very difficult for you to accept constructive cri- ticism from others? Do you have a tendency to jump to conlcusions in your interactions with others? Do you later apologize to some- one whose feelings ygg_may have hurt? Does it upset you a grgat deal when someone disagrees with you? When someone has hurt your feel- ings do you discuss the matter with that person? Do you avoid disagreeing with others because you are afraid they will get angry? When a problem arises between you and another person, are you able to discuss it without losing control of your emotions? NO SELDOM SOMETIMES 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 31. 32. 95 YES USUALLY Are you satisfied with the way you settle your differ- ences with others? Do you pout and sulk for a long time when someone upsets you? In meaningful conversation, are you aware of how you are feeling and reacting to what the other person is saying? Do you have difficulty trust- ing other people? In attempting to settle a mis— understanding, do you remind yourself that the other person could be right? Do you deliberately try to con- ceal your faults from others? Do you help others to under- stand you by saying how you think, feel, and believe? Is it difficult for you to con- fide in people? Do you have a tendency to change the subject when your feelings enter into a discussion? In conversation, do you let the other person finish talking before reacting to what he or she says? Do you find yourself not paying attention while in conversation with others? Do you ever try to listen for meaning when someone is talking? Do others seem to be listening when you are talking? NO SELDOM SOMETIMES 96 YES NO USUALLY SELDOM SOMETIMES 33. In a discussion is it difficult for you to see things from the other person's point of view? 34. Do you pretend you are listening to others when actually you are not really listening? 35. In conversation, can you tell the difference between what a person is saying (his words) and what he may be feeling? 36. While speaking, are you aware of how others may be reacting to what you are saying? 37. Do you feel that other people wished you were a different kind of person? 38. Do other people fail to understand your feelings? 39. Can you tell what kind of day another person may be having by Observing him? 40. Do you admit that you are wrong when you know that you are wrong about something? PLEASE CHECK TO MAKE SURE THAT YOU HAVE ANSWERED EACH ITEM. 10. 97 BELOW IS A LIST OF YOUR CLOSE FRIENDS. EACH OF YOUR CLOSE FRIENDS HAS BEEN PAIRED WITH YOU. ALSO, EACH OF YOUR CLOSE FRIENDS HAS BEEN PAIRED WITH EACH OTHER CLOSE FRIEND. FOR EACH PAIR, THERE ARE THREE QUESTIONS. PLEASE CONSIDER EACH ITEM CAREFULLY BEFORE ANSWERING. ANSWER.ALL ITEMS. 1. & a. In the last week (7 days), estimate how many times you think that these two persons have communicated with each other. Number of Times in Last Week b. On the scale below, estimate how similar (in general) you think these two persons are. Circle the one number that indicates how similar you think they are. The bigger the number you circle, the more similar you think they are. The smaller the number you circle, the more different you think they are. Very Very Different 1 2 3 4 5 6 7 8 9 Similar c. Suppose the first person wanted to get in touch with the second person of the pair. On the scale below, estimate how much effort , it would take the first person to_get in touch with the second 'person. Circle the one number that indicates how much effort you think it would take. Again, the bigger the number you circle, the more effort you think it.would take. The smaller the number you circle, the less effort you think it would take. Very Very Little 1 2 3 4 5 6 7 8 9 Much Effort Effort 98 In the last week (7 days), estimate how many times you think that these two persons have communicated with each other. Number of Time in Last Week On the scale below, estimate how similar (in general) you think these two persons are. Circle the one number that indicates how similar you think they are. Very Very Different l 2 3 4 S 6 7 8 9 Similar Suppose the first person wanted to get in touch with the second person. On the scale below, estimate how much effort it would take the first person to get in touch with the second person. Circle the one number that shows how much you think it would take. Very Little 1 2 3 4 5 6 7 8 9 very Eff t Much or Effort & In the last week (7 days), estimate how many times you think that these two persons have communicated with each other. Number of Times in Last Week On the scale below, estimate how similar (in general) you think these two persons aréT' Circle the one number that indicates how similar you think they are. Very Very Different 1 2 3 4 5 6 7 8 9 Similar Suppose the first person wanted to get in touch with the second person. On the scale below, Estimate how much effort it would take the first person togget in touch with the second person. Circle the one number that shows how much effort you think it would take . Very Very Little 1 2 3 4 S 6 7 8 9 Much Effort Effort 99 PLEASE: I. LOOK BACK THROUGH THE QUESTIONNAIRE TO MAKE SURE THAT YOU HAVE ANSWERED EVERY ITEM YOU WERE SUPPOSED T0. 2. RETURN THE COMPLETED QUESTIONNAIRE AT THE NEXT CLASS MEETING OR TO ROOM 423 SOUTH KEDZIE HALL. THIS HAS BEEN A LONG QUESTIONNAIRE. THANK YOU VERY MUCH FOR COMPLETING IT. YOUR TIME AND EFFORT ARE DEEPLY-APPRECIATED. FUTURE QUESTIONNAIRES WILL NOT BE AS LONG . THANK YOU APPENDIX III: WAVE #3 APPENDIX III: WAVE #3 MAE 1.0.. # Have # 3 MICHIGAN STATE WIVEIGITY College of Connunication Arts East Lansing, Michigan 48824 Depart-ant of Commication Dar Participant: This is the third of four questionnaires concerning your communication in close friendships. Although this questionnaire should not take you as lung to fill out as the previous one, it is inportant that you consider each question carefully and answer it sincerely. Sons of the its. from previous questionnaires are repeated here. Then is a reason for doing this that will be explained at the special ex- planatory session. It is important that you answer these items. Do not try to recall your previous answers. Just answer the repeated items accor- ding to how you presently feel. If an item is not clear or if you have any questions about any of the items, please ,call me. Office Phone: 355-1862 Home Phone: 355:0789 You should be able to contact me or leave a message for me at these numbers. Please do not call before 7:30 in the morning or after 10:30 at night. Remember that all information you give me will be kept strictly confi- dential. PLEASE RETURN THIS QlESTIONNAIRE AT THE NEXT MEETING OF THIS CLASS, OR TO MON “23 SOUTH KEDZIE HALL. Thank you, ,l. .3 jg, I‘4J/L f.l.'n. 4'" Mac Parks Principal Investigator 100 101 1. BELOW IS A SERIES OF'ITEMS. YOUR JOB IS TO INDICATE HOW MUCH YOU AGREE OR DISAGREE WITH EACH ITEM. CIRCLE THE ONE NUMBER WHICH INDICATES HOW HUGH'YOU AGREE OR DISAGREE WITH EACH ITEM. THE LARGER THE NUMBER YOU CIRCLE, THE MORE YOU AGREE WITH THE ITEM. THE SMALLER THE NUMBER YOU CIRCLE, THE LESS YOU AGREE WITH THE ITEM. BE SURE TO CIRCLE ONLY ONE NUMBER FOR EACH ITEM. PLEASE RESPOND TO EACH ITEM INDIVIDUALLY. a. It is extremely important to me to have a relationship with another person in which we can share personal information about ourselves. Strongly Strongly Disagree 1 2 a use 7.3 9 Agree b. It is extremely important to me to have a relationship with another person in which there is a great deal of’mutual trust. Strongly Strongly Disagree 1 2 3 4 5 6 7 B 9 Agree c. Having a special and lasting relationship with another person is extremely important to me. Strongly Strongly Disagree 1 2 3 u 5 6 7 8 9 Agree d. It is extremely important to me to have a relationship with another person in which both of us could count on each other for help when needed.’ Strongly 7 Strongly Disagree 1 2 3 u 5 6 7 8 9 Agree s. It is extremely important to me to have a relationship with another person in which there is a great deal of mutual liking. Strongly Strongly Disagree 1 2 a u 5 s 7 s 9 Agree 102 2. Into" IS A LIST or ACTIVITIES. YOUR JOB Is To ESTIMATE How nucu TIME (IN HOURS) YOU SPEND on EACH ACTIVITY on AN AVERAGE WEEKDAY AND on AN AVERAGE WEEKEND DAY IN EACH ACTIVITY. Si? aces not exc333'2u hours. Be sure tEEtyour lIst for each AVERAGE AVERAGE ACTIVITY: WEEK DAY WEEKEND DAY As "GEM: EGIGVISIGI "" hm. hme B. Reading books, magazines, ‘ newspapers, etc. --- hrs. hrs. C. Listening to the Radio and Stereo (List only the hours when you did nothing else except listen) --- hrs. hrs. D. Talking with persons who are friends, Egt_who are not close friends --- hrs. hrs. B. Talking with persons who are neither close friends or other types of friends --- hrs. hrs. F. Time Spent Alone -- that is, time you were not actually with one or more other persons. Include hours spent sleeping in this category --- hrs. hrs. r.-. g 103 Now, think about the number of times you have moved from one town to another. IN THE LAST FIVE YEARS, HOW MANY TIMES HAVE YOU MOVED FROM ONE TOWN TO ANOTHER TOWN OR CITY? LIST EACH MOVE. LIST ONLY THOSE TIMES WHEN YOU MOVED PROM ONE TOWN TO ANOTHER. no NOT LIST MOVES WITHIN THE SAME TOWN OR CITY. l. Moved from to . 2. Moved from to . 3. Moved from to . u. Moved from to . 5. Moved from to . 6. Moved from to . 7. Moved from to . 8. Moved from to . 9. Moved from to . 10. Moved from to . ll. Moved from to v W , 12. Moved from to . 13. Moved from to . lu. Moved from to . 15. Moved from to ‘+. HAVE YOU ? Listed only moves from one town to another? Listed only those moves in the last five years? IF YOU NEED MORE SPACE, CONTINUE ON THE BACK OF THIS PAGE. M. 104 IN THE LAST FIVE YEARS, HOW MANY TIMES HAVE YOU MOVED FROM ONE PLACE TO ANOTHER HITHIN THE SAME TOWN? EIST EACH CHANGE OF ADDRESS. 55 NOT EIST MOVES EROM ONE TOWN TO ANOTHER. 1H. 15. IF YOU CHANGED ADDRESSES MORE THAN ONCE WHILE LIVING IN THE SAME TOWN OR CITY, USE ONE LINE OF THE LIST BELOW FOR EACH MOVE. NEED MORE I changed I changed I changed I changed I changed I changed I changed I changed I changed I chmged I changed I changed I changed I changed Iwmmd HAVE YOU ? SPAC§;‘CfifiTIfifiE ofi‘THE addresses addresses addresses addresses addresses addresses addresses addresses addresses addresses addresses addresses addresses addresses addresses when when when when when when when when when when when when when when when I I lived lived lived lived lived lived lived lived lived lived lived lived lived lived lived BACK OFwTHIS PAGE. in IF YOU in in in in in in in in in in in in in in Listed only moves within the same town? Listed only moves within the last five years? Listed only one change of address per line? 5. 105 BELOW IS A LIST OF YOUR CLOSE FRIENDS. EACH OF YOUR CLOSE FRIENDS HAS BEEN PAIRED WITH YOU. ALSO, EACH OF YOUR CLOSE FRIENDS HAS BEEN PAIRED WITH EACH OTHER CLOSE FRIEND. FOR EACH PAIR, THERE ARE THREE QUESTIONS. PLEASE CONSIDER EACH ITEM CARE- FULLY BEFORE ANSWERING. ANSWER ALL ITEMS. . _A 1. E E' a. In the last week (7 days), estimate how many times you think that H these two persons have communicated with eaCE_other. 4 Number of Times in Last Week. b. On the scale below, estimate how similar (in general) you think these two persons are.‘éCircle the one number that indicates how similar you think they are. The bigger the number you circle, the more similar you think they are. The smaller the number you circle, the more different you think they are. Very Very Different l 2 3 u 5 6 7 8 9 Similar c. Suppose the first person wanted to get in touch with the second person of the pair. 0n the scale below, estimate how much effort it would take the first person to get in touch with the second’ " rson. CirCIe the one number th§§gindicatesfihow muEh effgrt it would take. Again, the bigger the number you circle, the more effort you think it would take. The smaller the number you circle, the less effort you think it would take. Very Very Little 1 2 3 u 5 6 7 8 9 Much Effort Effort 106 C. In the last week (7 days), estimate how many times you think that these two persons have communicated with each other. Number of Times in Last Week. On the scale below, estimate how similar (in general) you think these two persons are. Circle the one number that indicates how similar you think they are. Very Very Different l 2 3 4 5 6' 7 8 9 Similar Suppose the first person wanted to get in touch with the second person. 0n the scale below, estimate how much effort it would take the first person to t in touCh with the second person. CirEIe the one number that éhows much you think it would take. very Very Little 1 2 3 u 5 6 7 8 9 Much Effort Effort 8 a. C. In the last week (7 days), estimate how many times you think that these two persons have communicated with each other. Number of Times in Last Week. On the scale below, estimate how similar (in general) you think these two persons are. Circle the one number that indicates how similar you think they are. Very Very Different l 2 3 u S 6 7 8 9 Similar Suppose the first person wanted to get in touch with the second person. On the scale below, estimate how much effort it would take the first person to get in touEh with The second person. CircIé the one number that shows-how much effort you think’it would take. Very Very Little 1 2 3 u 5 6 7 8 9' Much Effort Effort 107 PLEASE: I. LOOK BACK THROUGH THE QUESTIONNAIRE TO MAKE SURE THAT YOU HAVE ANSWERED EVERY ITEM YOU WERE SUPPOSED T0. fiuai=a¥§ 2. RETURN THE COMPLETED QUESTIONNAIRE AT THE NEXT CLASS MEETING OR TO ROOM “23 SOUTH KEDZIE HALL. THERE WILL ONLY BE ONE MORE QUESTIONNAIRE AFTER THIS ONE. IT WILL BE SHORTER THAN THE PREVIOUS TWO. YOUR TIME AND EFFORT ARE VERY GREATLY APPRECIATED. THANK YOU. APPENDIX IV: WAVE #u I18 1.. APPENDIX IV: WAVE #14» § Name: Wave # u I.D. # MICHIGAN STATE UNIVERSITY College of—Oommunication Arts napartnant of Communication East Lansing, Michigan “882u Dear Participant: l A This is the final questionnaire concerning your communication in close , friendships. It should take you somewhat less time to complete than did the * I previous two questionnaires. I realize that you have already given us a great . deal of your»the and attention. I deeply appreciate this. Like previous questionnaires, it is important that you consider each item carefully and answer it sincerely. Some of'the items from previous questionnaires are repeated here. There is a reason for doing this that will be explained at the special explanatory session. It is important that you answer these items. Do not try to recall your previous answers. Just answer the repeated items according to how you presently feel. If an item is not clear or if you have any questions about any of the items, please call me. Office Phone: 355-1862 Home Phone: 355-0789 You should be able to contact me or leave a message for>me at these numbers. Please do not call before 7:30 in the morning or after 10:30 at night. Remember that all information you give me will be kept strictly confiden- tial. You will be notified as to the time, place, and date of the special explanatory session. PLEASE RETUW THIS QUESTIONNAIRE AT THE NEXT MEETING OF THIS CLASS, OR TO ROOM “23 SOUTH KEDZIE HALL. Thank you, V ma, PW..,.£-.- 4.. Mac Parks Principal Investigator 108 109 1. IN THE RLAST FIVE YEARS, How MANY TIMES HAVE YOU MOVED FROM om: TOWN To ANOTHER EAEH'To‘vs—m os 2"W EN YOU MOVE b ' "rRo' "r 1"‘o‘N'B' MRT’WN'or—fisr "' TMOVES WITHIN THE SAME TOWN OR CITY. l. Moved from to . 2. Moved from to 3. Moved from to . u. Moved from to 5. Moved from to f 6. Moved from to . 7. Moved from to . 8. Moved from to . Q. Moved from to . 10. Moved from to . 11. Moved from to . 12. Moved from v_ to . 13. Moved from I. to . lu. Moved from to . 15. Moved from tow . HAVE YOU 7 Listed only moves from one town to another? Listed only those moves in the last five years? IF YOU NEED MORE SPACE, CONTINUE ON THE BACK OF THIS PAGE. 2. 110 IN THE LAST FIVE YEARS, HOW MANY TIMES HAVE YOU MOVED FROM ONE PLACE TO ANOTHER LIST EACH CHANGE OF ADDRESS. DO NOT LISI MOVES PROM ONE H N A R. IF YOU CHANGED ADDRESSES MORE THAN ONCE WHILE LIVING IN THE SAME TOWN 0R CITY, USE ONE LINE or THE LIST BELOW FOR EACH MOVE. NOE—6m CONT! changed changed changed changed changed changed changed changed changed changed changed changed changed changed changed HAVE YOU ? addresses addresses addresses addresses addresses addresses addresses addresses addresses addresses addresses addresses addresses addresses addresses when when when when when when when when when when when when when when when Listed only moves Listed only one change of address per line? S PAGE. I lived I lived I lived I lived I lived I lived I lived I lived I lived I lived I lived I lived I lived I lived I lived within the same town? Listed only moves within the last five years? in in in in in in in in in in in in in in IF you NEED MORE SPACE, .g..-n._—..*e._~ I " Tia—Ni En: 111 3. ESTIMATE THE ANNUAL INCOME OF YOUR FAMILY. S u. DELON IS A LIST OF YOUR CLOSE FRIENDS. EACH OF YOUR OLSOE FRIENDS HAS BEEN PAIRED WITH You. ALSO, EACH OF YOUR CLOSE FRIENDS HAS BEEN FAIRED WITH EACH OTHER CLOSE FRIEND. FOR EACH PAIR OF FERSONS THERE IS ONE QUESTION. FLEASE CONSIDER IT CAREFULLY BEFORE ANSWERING. ANSWER ALL ITEMS? l. 8 O In the last week (7 days), estimate how many times you think that these two persons have communicated with each other. Number of Times in Last Week 2. 8 . In the last week (7 days), estimate how many times you think that these two persons have communicated with each other. Number of Times in Last Week 3. I 8 . In the last week (7 days), estimate how many times you think that these two persons have communicated with each other. Number of Times in Last Week “0 8 0 In the last week (7 days), estimate how many times you think that these two persons have communicatediwIth eaéh other. Number of Times in Last Week 5. 8 . In the last week (7 days), estimate'how many times you think that these two persons have communicatedfiwith each other. Number of Times in Last Week 112 In the last week (7 days), estimate how many times you think that these two persons have communicated with each other. Number of Times in Last Week In the last week (7 days), estimate how many times you think that these two persons have communicated with each other. Number of Times in Last Week In the last week (7 days), estimate how many times you think that these two persons have communicated with each other. Number of Times in Last Week In the last week (7 days), estimate how many times you think that these two persons have communicated with each other. Number of'Times in Last Week In the last week (7 days), estimate how many times you think that these two persons have communicated with each other. Number of Times in Last Week 5. 113 BELOH Is THE LIST OF'TOUR CLOSE FRIENDS THAT YOU FROVIDED BEFORE. HOW MANY HOURS AND MINUTES YOU SPENT TALKING wITH EACH CLOSE FRIEND‘IN"""T'HE‘ " fifi' 'HEE""""N. "PIETSE TWRY TO BE Ir ACCURATE AS FOSS‘I BLE. 1. 2. 17. 18. 19. 20. 21. 22. HOURS HOURS HOURS HOURS HOURS 'HOURS HOURS HOURS HOURS HOURS HOURS HOURS HOURS HOURS HOURS HOURS HOURS HOURS HOURS HOURS HOURS HOURS I HHHHIHH MINUTES MINUTES MINUTES MINUTES MINUTES MINUTES MINUTES MINUTES MINUTES MINUTES MINUTES MINUTES MINUTES MINUTES MINUTES MINUTES MINUTES MINUTES MINUTES MINUTES MINUTES MINUTES ESTIMATE 6. 11” HOW MANY OUARTERS HAVE YOU BEEN GOING Tq_gICHIGAN STATE? COUNT UP ONLY THOSE QUARTERS IN COLLEGE THAT You SPENT AT THIS SCHOOL. NUmber of Quarters at M.S.U. BELOW ARE A SERIES OF QUESTIONS CONCERNING HOW YOU FEEL ABOUT THINGS IN GEN- EEKE. BENEATH EACH ITEM IS A SCALE. CIRCLE THE ONE NUMBER THAT INDICATES ‘HOW'YOU FEEL ABOUT THE ITEM. THE BIGGER THE NUMBER THE CIRCLE, THE MORE YOU ISREE WITH THE ITEM. THE SMALLER THE NUMBER YOU CIRCLE, THE MORE YOU DISAGREE ‘EITH THE ITEM. —Circle only one number for each item. Please answer each item. a. MOST PUBLIC OFFICIALS (PEOPLE IN PUBLIC OFFICES) ARE NOT REALLY INTERESTED IN THE PROBLEMS OF THE AVERAGE PERSON. Strongly Strongly Disagree 1 2 3 u 5 6 7 8 9 Agree b. NOWADAYS A PERSON HAS TO LIVE PRETTY MUCH FOR TODAY AND LET TOMORROW TAKE CARE OF ITSELF. Strongly Strongly Disagree 1 2 3 u 5 6 7 8 9 Agree c. THE AVERAGE PERSON IS PROBABLY BETTER OFF TODAY THAN HE OR SHE EVER WAS. Strongly Strongly Disagree 1 2 3 u s 6 7 8 9 Agree d. IT'S HARDLY FAIR TO BRING CHILDREN INTO THE WORLD WITH THE WAY THINGS LOOK FOR THE FUTURE. Strongly Strongly Disagree 1 2 a u s 6 7 8 9 Agree e. THESE DAYS A PERSON DOESN'T REALLY KNOW WHOM HE CAN COUNT ON. Strongly Strongly Disagree 1 2 3 u 5 6 7 8 9 Agree 115 ARE THERE ANY COMMENTS THAT YOU WOULD LIKE TO MAKE CONCERNING THE STUDY ITSELP OR CONCERNING THE INFORMATION YOU WERE ASKED? THIS WAS THE FINAL QUESTIONNAIRE FOR THE STUDY. I SINCERELY APRPECIATE THE TIME, THOUGHT, AND EFFORT YOU HAVE GIVEN. YOU HAVE BEEN VERY HELPFUL TO ME. A SPECIAL EXPLANATORY SESSION WILL BE SCHEDULED AND ANNOUNCED IN YOUR CLASS. THANK YOU. RETURN THE COMPLETED QUESTIONNAIRE AT THE NEXT CLASS MEETING OR TO ROOM W23 SOUTH KEDZIE HALL. APPENDIX V: DATA TRANSFORMATIONS APPENDIX V: DATA TRANSFORMATIONS Descriptive statistics for the variables revealed that many of the variables were severely skewed either positively or negatively. In order to correct for this difficulty, each variable was subjected to a logarith- mic transformation. In cases where the variable was positively skewed, the transformation was performed directly on the variable. In cases where the variable was negatively skewed, the distribution of the variable was first reversed (making it positively skewed) and then the logarithm of the variable was computed. The choice as to whether to use the variable or its logarithm for later analysis was made by comparing the skewness of the variable to the skewness of its logarithm. In each case, the form possessing the least absolute skewness was used for later analysis. Table 7 presents the skew for each variable and its logarithmic transformation in the model. 116 117 Table 7. Skewness of Variables and Their Logarithms. Skew of Skew of Variable Variable Logarithm Network Size + .u96* — .556 Memberships in Voluntary Associations +1.861 + .375* Socioeconomic Status -l.019 - .273* Time/Mass Media + .824 — .760* Time/Non-Close Friends +1.667 - .139* Time/Non-Friends + .989 - .950* Time/Alone — .309* —3.880 Communication Skills + .007* - .400 Desire for Participation -2.Ouu + .235* Integration +2.588 - .1u3* Similarity (Perceived) + .039* - .u66 Effort (Perceived) + .040* -l.322 Mobility +1.352 - .180* *This form of the variable was used for analysis. APPENDIX VI: PROCEDURES FOR THE ESTIMATION OF OPPORTUNITY APPENDIX VI: PROCEDURES FOR THE ESTIMATION OF OPPORTUNITY The unmeasured variable of opportunity (Y1) was estimated as the lin— ear combination of the measured variables hypothesized to underlie it. This was done according to the following two steps. First, the exogenous variables of desire (X5) and communication skills (X6) and the variables hypothesized to underlie opportunity (X7 to X13) were used as independent variables in a multiple regression procedure on the dependent variable of network size (Xu). Second, the standardized regression coefficients (beta weights) for the hypothesized underlying variables were used in combination with the underlying variables themselves to form a linear equation which predicted opportunity (Y1). The latter step can be more fully outlined by presenting both the general linear equation and then the specific values for the regression coefficients. In its general form, the equation to predict opportunity is: Y1 = p17x7 + p18X8 + p19x9 + pl,lOXlO + p1,11X11 + p1,12X12 + p1,13x13 Where: Y1 = Opportunity X7 = Number of Memberships in Voluntary Associations X8 = Socioeconomic Status X9 = Time Spent with Mass Media Sources X = Time Spent with Non-Close Friends 10 . Xll = Time Spent Alone Xl2 = Level of Residential Mobility X13 = Time Spent with Non-Friends p = Standardized Regression Coefficients (Path Coefficients) 118 119 The first step outlined above yielded specific values for the stand- ardized regression coefficients. When these specific values are substi- tuted into the general predictor equation above, an estimate of opportunity is derived. The specific standardized and unstandardized regression co- efficients for the variables hypothesized to underlie opportunity are given in the table below: Table 8- Regression Coefficients for Variables Underlying Opportunity Standardized Unstandardized Variable Regression Coefficient Regression Coefficient V01. Assoc. .16870 2.08013 SES -.10126 —.84205 Time/Mass Media .18658 2.95303 Time/Non-Close .11235 l.u6621 Time/Alone -.l787u -.0u656 Mobility .158u8 l.u9168 Time/Non-Friends -.03867 .39252 APPENDIX VII: PROCEDURES FOR THE ESTIMATION OF PATHS FROM OPPORTUNITY TO UNDERLYING VARIABLES APPENDIX VII: PROCEDURES FOR THE ESTIMATION OF PATHS FROM OPPORTUNITY TO UNDERLYING VARIABLES Opportunity (Y1) was hypothesized to be the common factor of several underlying variables (X7 to X8). Thus, the estimation of the paths from opportunity to these variables was much like factor analysis. In fact, 31 these path coefficients are very much like factor loadings. & To estimate the paths from opportunity to the hypothesized underlying ‘4 variables, the following procedure was utilized. First, the standardized regression co-efficients of the underlying variables (X7 to X13) were ob- tained by applying a multiple regression procedure where the underlying variables were independent and the dependent variable was network size (X4). These values are listed in Table 8 in the previous Appendix (VI). Second, these beta weights were arrayed in a 1x7 matrix which was pre- multiplied by the zero-order correlation matrix of the seven hypothe- sized variables. The result of this matrix operation yielded estimates for each of the paths from opportunity to the underlying variables. A more complete description of this procedure and a more detailed theoretic rationale behind it are presented in Van de Geer (1971). 120 APPENDIX VIII: PROCEDURES FOR THE ESTIMATION OF THE RELATIONSHIP BETWEEN PERCEIVED SIMILARITY AND INTEGRATION APPENDIX VIII: PROCEDURES FOR THE ESTIMATION OF THE RELATIONSHIP BETWEEN PERCEIVED SIMILARITY AND INTEGRATION The relationship between perceived similarity and network integration was hypothesized to be non-recursive. That is, the relationship was be- lieved to be reciprocal. As a result, the typical regression techniques employed to estimate other paths in the model were insufficient. Because of the lack of the necessary software to deal with non-recursive paths, several improvised procedures were employed. These are described below. Estimating Paths to Integration Integration was hypothesized to be a function of the following four variables: 1) network size; 2) residential mobility; 3) perceived effort; and 4) perceived similarity. Put in equation form, we can write the hy- pothesis in the following manner: X X (l) 1 = pluxu + p1,12 12 + p12x2 + p13x3 + pluU Where: >< Network Integration Perceived Similarity Perceived Effort Network Size Residential Mobility Residual Term (Error) Hts)» M CXXX By multiplying this structural equation by the exogenous variables, esti- mating equations can be Obtained. In addition to the exogenous variables of desire (X5), communication skills (X6) and opportunity (Y1), age (which we will designate as X0) of the subject was employed to derive the estimating 121 122 equations. This latter variable was used simply to get an additional esti— mating equation. The structural equation when multiplied by the four ex- ogenous variables yields the following four estimating equations: (By XO)’ ”10 = piu”ou + p1,12”o,12 + p12”O2 + p13”03 (2) (By X5)‘ ”15 = p1u”5u + p1,12”5,12 + p12”52 + p13”53 (3) (By Xe): ”16 = p1u”su + p1,12”6,12 + p12”e2 + p13”63 (”) (By Y1): r1y = pluryu + pl,12ry,l2 + pler2 + plary3 (5) It should be noted that the residual and its path in the structural equa- tion drop out when multiplied by the exogenous variables since the corre— lation between a residual and an exogenous variable is assumed to be zero. If the four estimating equations (2—5) above are segmented into matrices, the following identity is obtained: ”10 ”OH ”0,12 ”02 ”03 ”In ”15 ”SH ”5,12 ”52 ”53 p1,12 = x (6) ”16 ”SH ”5,12 ”62 ”63 p12 ”1y ”yu ”y,12 ”y2 ”y3 p13 All of the correlations (the "r's" are known. This leaves only the path coefficients (the "p's" are unknowns.) By rearranging the matrices we can solve for these unknowns. If we label the three matrices above as "A”, "B" and "C" from left to right, we have the following identities: A = BC (7) And C = B x A (8) 123 That is, C (the matrix of unknown path coefficients) equals the product of the inverse of matrix B and matrix A. When these operations are per- formed with the actual values of the correlations, the following results were obtained: plu .H293 p —.3u3u C = 1’12 (9) p12 —.0227 p13 -.5670 These procedures have allowed us to estimate the path coefficients for all paths leading to network integration. Our particular interest here is with p12, the path from similarity (X2) to network integration (X1). As equation 9 indicates, this estimate was -.0227. Estimating the Path to Similarity Our interest now turns to the estimation of the other half of the non- recursive relationship-~the path from integration to similarity. In the hypothesized model, similarity is wholly a function of integration. Thus, the structural equation for perceived similarity is: x x1 + p2vV (10) 2 = p21 Where: Network Integration Perceived Similarity Residual Term (Error) Path coefficient NH M II II II 'U<><>< Again, by multiplying this structural equation by the exogenous variables, four estimating equations are obtained: 124 (By X0): r02 = p2lr01 (11) (By X5): r52 = p2lr51 (12) (By X6): r62 = p2lr61 (13) (By Y1): ry2 = p2lryl (lu) Where: X = Age of Subject 0 . X5 = Desire X = Communication Skills 6 _ . Yl - Opportunity Since all the correlations (the "r's") in these equations (ll—la) are known, we have p21, the path from integration to perceived similarity, as the only unknown. Further, we have four estimates of this path: Table 9. Estimates of p21. Estimating Estimate Equation of p21 ll .21 12 10.5 13 -.29 1H 14.67 The best available estimate of p21 is the mean of the four estimates listed in Table 9. This mean is 3.77. Thus, this is the value of the path coef- ficient for the path from integration to perceived similarity.