Modeling Dyadic and Interdependent Data in the Developmental and Behavioral Sciences

by Noel A. Card (Editor), James P. Selig (Editor), Todd D. Little (Editor)

This book reviews methods of conceptualizing, measuring, and analyzing interdependent data in developmental and behavioral sciences. Quantitative and developmental experts describe best practices for modeling interdependent data that stem from interactions within families, relationships, and peer groups, for example. Complex models for analyzing longitudinal data, such as growth curves and time series, are also presented. Many contributors are innovators of the techniques and all are able to clearly explain the methodologies and their practical problems including issues of measurement, missing data, power and sample size, and the specific limitations of each method. Featuring a balance between analytic strategies and applications, the book The Actor-Partner Interdependence Model for analyzing influence between two individuals The Intraclass Correlational Approach for analyzing distinguishable roles (parent-child) or exchangeable (same-sex) dyadic data The Social Relations Model for analyzing group interdependency Social Network Analysis approaches for relationships between individuals This book is intended for graduate students and researchers across the developmental, social, behavioral, and educational sciences. It is an excellent research guide and a valuable resource for advanced methods courses.

451 pages, Kindle Edition

First published January 1, 2008

About the author

Noel A. Card, Ph.D., is Associate Professor in Family Studies and Human Development at the University of Arizona. His areas of interest include child and adolescent social developmental and quantitative research methods. He has received the Society for Research in Child Development Early Career Research Contributions Award and is an elected member of the Society of Multivariate Experimental Psychology.