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Dyadic Data Analysis

David A. Kenny, Deborah A. Kashy, William L. Cook

Buch (gebundene Ausgabe, Englisch)
Buch (gebundene Ausgabe, Englisch)
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Interpersonal 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.

David A. Kenny, Department of Psychology, University of Connecticut, Storrs, USA. Winner of the Distinguished Scientist Award from the Society of Experimental Social Psychology 2012. Deborah A. Kashy, Department of Psychology, Michigan State University, East Lansing, USA William L. Cook, Maine Medical Center, Center for Psychiatry Research, Portland, ME, USA


Einband gebundene Ausgabe
Seitenzahl 458
Erscheinungsdatum 01.08.2006
Sprache Englisch
ISBN 978-1-57230-986-9
Reihe Methodology in the Social Scie
Verlag KNV Besorgung
Maße (L/B/H) 23.1/16.1/3 cm
Gewicht 762 g
Abbildungen farbige, schwarzweisse Abbildungen


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  • 1. Basic Definitions and Overview Nonindependence Basic Definitions Data Organization A Database of Dyadic Studies 2. The Measurement of NonindependenceInterval Level of MeasurementCategorical MeasuresConsequences of Ignoring NonindependenceWhat Not to DoPower Considerations3. Analyzing Between- and Within-Dyads Independent VariablesInterval Outcome Measures and Categorical Independent Variables Interval Outcome Measures and Interval Independent Variables Categorical Outcome Variables 4. Using Multilevel Modeling to Study DyadsMixed-Model ANOVAMultilevel-Model EquationsMultilevel Modeling with Maximum LikelihoodAdaptation of Multilevel Models to Dyadic Data5. Using Structural Equation Modeling to Study DyadsSteps in SEM Confirmatory Factor Analysis Path Analyses with Dyadic Data SEM for Dyads with Indistinguishable Members 6. Tests of Correlational Structure and Differential VarianceDistinguishable Dyads Indistinguishable Dyads 7. Analyzing Mixed Independent Variables: The Actor–Partner Interdependence ModelThe Model Conceptual Interpretation of Actor and Partner Effects Estimation of the APIM: Indistinguishable Dyad MembersEstimation of the APIM: Distinguishable Dyads Power and Effect Size Computation Specification Error in the APIM 8. Social Relations Designs with Indistinguishable MembersThe Basic Data StructuresModelDetails of an SRM AnalysisModelSocial Relations Analyses: An Example9. Social Relations Designs with RolesSRM Studies of Family RelationshipsDesign and Analysis of StudiesThe Model Application of the SRM with Roles Using Confirmatory Factor AnalysisThe Four-Person Design Illustration of the Four-Person Family Design The Three-Person DesignMultiple Perspectives on Family RelationshipsMeans and Factor Score EstimationPower and Sample Size10. One-with-Many DesignsDesign IssuesMeasuring NonindependenceThe Meaning of Nonindependence in the One-with-Many DesignUnivariate Analysis with Indistinguishable PartnersUnivariate Estimation with Distinguishable PartnersThe Reciprocal One-with-Many Design 11. Social Network AnalysisDefinitions The Representation of a Network Network Measures The p112. Dyadic IndexesItem Measurement IssuesMeasures of Profile SimilarityMean and Variance of the Dyadic IndexStereotype AccuracyDifferential Endorsement of the Stereotype Pseudo-Couple AnalysisIdiographic versus Nomothetic AnalysisIllustration 13. Over-Time Analyses: Interval OutcomesCross-Lagged Regressions Over-Time Standard APIM Growth-Curve Analysis Cross-Spectral Analysis Nonlinear Dynamic Modeling 14. Over-Time Analyses: Dichotomous OutcomesSequential AnalysisStatistical Analysis of Sequential Data: Log-Linear AnalysisStatistical Analysis of Sequential Data: Multilevel Modeling Event-History Analysis 15. Concluding CommentsSpecialized Dyadic Models Going Beyond the Dyad Conceptual and Practical Issues The Seven Deadly Sins of Dyadic Data AnalysisThe Last Word