Dyadic Data AnalysisInterpersonal phenomena such as attachment, conflict, person perception, helping, and influence have traditionally been studied by examining individuals in isolation, which falls short of capturing their truly interpersonal nature. This book offers state-of-the-art solutions to this age-old problem by presenting methodological and data-analytic approaches useful in investigating processes that take place among dyads: couples, coworkers, or parent-child, teacher-student, or doctor-patient pairs, to name just a few. Rich examples from psychology and across the behavioral and social sciences help build the researcher's ability to conceptualize relationship processes; model and test for actor effects, partner effects, and relationship effects; and model the statistical interdependence that can exist between partners. The companion website provides clarifications, elaborations, corrections, and data and files for each chapter. |
Contents
1 Basic Definitions and Overview | 1 |
2 The Measurement of Nonindependence | 25 |
3 Analyzing Between and WithinDyads Independent Variables | 53 |
4 Using Multilevel Modeling to Study Dyads | 78 |
5 Using Structural Equation Modeling to Study Dyads | 100 |
6 Tests of Correlational Structure and Differential Variance | 119 |
The ActorPartner Interdependence Model | 144 |
8 Social Relations Designs with Indistinguishable Members | 185 |
10 OnewithMany Designs | 263 |
11 Social Network Analysis | 296 |
12 Dyadic Indexes | 317 |
Interval Outcomes | 342 |
Dichotomous Outcomes | 381 |
15 Concluding Comments | 406 |
427 | |
445 | |
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Common terms and phrases
actor and partner actor effect actor variance ANOVA anxiety APIM average behavior between-dyads variable Chapter chi-square child classroom coded compute consider couples covariance data set degrees of freedom discussed distinguishable dyads dyad members dyadic data dyadic index dyadic reciprocity equal equation error variance estimate example data family members father focal person gender grand mean I-SAT independent variable indicates individual interaction intercept interpersonal intraclass correlation Kenny latent variable level of measurement level-1 marital satisfaction maximum likelihood measure members are distinguishable method MLwiN mother multilevel models negative nonindependence Note null hypothesis number of dyads one-with-many design outcome variable pairwise parameters partner effects partner variance predictor variables PROC MIXED random relationship effect relationship variance role roommates sample similarity slope SPSS SRM design statistically significant stereotype accuracy strategy structural equation modeling subgroups Table tion types unit of analysis vari within-dyads variable zero
Popular passages
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Page 436 - John, OP, Kenny, DA, Bond, M. H., & Robins, RW (2004). Reconceptualizing individual differences in self-enhancement bias: An interpersonal approach. Psychological Review, 111, 94-110.
Page 432 - Wiley. Gonzalez, R., & Griffin, D., (1999). The correlational analysis of dyad-level data in the distinguishable case. Personal Relationships, 6, 449469. Gonzalez, R., & Griffin, D.
Page 432 - WH, & Roberts, KH (1984). Hypothesized interdependence, assumed independence. Academy of Management Review, 13, 133-147, Goldstein, H.
Page 431 - Integrating family theory, family scores, and family analysis. In TW Draper & AC Marcos (Eds.), Family variables: Conceptualization, measurement, and use (pp.