ISSN 2043-8087
Journal of Experimental Psychopathology
 Volume 2, Issue 2, 95-138, 2011
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Tracing the Interpersonal Web of Psychopathology: Dyadic Data Analysis Methods for Clinical Researchers

Authors
Pamela Sadler (a), Nicole Ethier (b) and Erik Woody (b)
(a) Wilfrid Laurier University
(b) University of Waterloo

Volume 2, Issue 2, 2011, Pages 95-138
DOI: http://dx.doi.org/10.5127/jep.010310

Abstract
Recent advances in dyadic data analysis techniques, which treat the dyad, rather than the individual, as the unit of analysis, offer great potential for clinical researchers studying psychopathology. Accordingly, the present article provides readers with a foundation for understanding how the web of interpersonal processes surrounding psychopathology can be modeled and analyzed. The authors start by describing why the analysis of dyadic behaviour may be particularly important for clinical researchers and how issues of dependence that lie at the heart of dyadic data may be productively studied. Next, they describe design issues to consider when studying the interactions of dyads, as well as different kinds of outcome and predictor variables and their data-analytic implications. They introduce the actor-partner interdependence model (APIM), and explain in detail how to estimate it using structural equation modeling (SEM) for both distinguishable and indistinguishable dyads. Extensions of the basic APIM to allow for moderation and mediation, as well as alternative dyadic models involving dyadic latent variables are also covered. Toward the end of the article, the authors describe various approaches for incorporating psychopathology into dyadic SEMs and provide a list of basic questions for clinical researchers to consider when setting up a dyadic model for data analysis.

Table of Contents
Introduction
  What Happens to the Data when People Interact
  Dependent Data: Kludges versus Opportunities
  Some Basic Dyad Design Issues
  Different Kinds of Dyadic Variables and their Implications for Data Analysis
    Non-dyadic outcome variable.
    Between-dyads outcome variable.
    Within-dyads outcome variable.
    Mixed outcome variable.
  Between-Dyads, Within-Dyads, and Mixed Variables as Predictors
  A Note on SEM versus MLM
Dyadic SEM Models
  The Basic APIM
  Estimation of the APIM for Dyads with Distinguishable Members
  Tests of Sex Differences and the Empirical Evaluation of Distinguishability
  Other Comparisons
  Expanding the APIM: Between-Dyads Predictors and Moderation
  Expanding the APIM: Mediation
  Models Involving Dyadic Latent Variables
  Estimation of the APIM for Dyads with Indistinguishable Members Guidelines for using Dyadic Analyses in Studies of Psychopathology
  Some Basic Questions in Setting up a Dyadic Model for Data Analysis
  Other Possibilities
Acknowledgements
References
Appendix A: Downloadable Dataset and Amos Input Diagrams (.amw)
Appendix B: Using the Bias-Corrected Bootstrap in Amos to Evaluate the APIM with Mediation
Appendix C: Steps for the SEM Analysis of Indistinguishable Dyads and Examples
  Steps
  Example 1: APIM with mediation for indistinguishable dyads.
  Example 2: Dyadic model with a mixed latent variable for indistinguishable dyads.

Correspondence to
Pamela Sadler, Ph.D. Department of Psychology, Wilfrid Laurier University, 75 University Avenue West, Waterloo, ON N2L 3C5, CANADA.

Keywords
statistical dependence; dyadic dependence; distinguishable dyads; exchangeable dyads; interchangeable dyads

Dates
Received 3 Aug 2010; Revised 25 Oct 2010; Accepted 26 Oct 2010; In Press 5 May 2011







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