Modeling Dyadic and Interdependent Data in the Developmental and Behavioral Sciences

Noel A. Card is Assistant Professor of Family Studies and Human Development at the University of Arizona. He received his PhD in Clinical Psychology from St. John’s University. James P. Selig is a Doctoral Candidate in Quantitative Psychology at the University of Kansas.Todd D. Little is Director of the Research Design and Analysis Unit and Director of the Quantitative Psychology doctoral training program at the University of Kansas. He received his PhD in Developmental Psychology from the University of California at Riverside.

"There are relatively few guides for researchers who explore the interdependence of human functioning… This book will clearly rectify that limitation… This book... [is] …of great value to many psychologists… [and] for doctoral seminars in developmental psychology or biostatistics...I highly recommend this book." -Theresa Thorkildsen, University of Illinois, Chicago"In its groundbreaking translation of multiple methods to its topic, this is a very important book for those who conduct developmental research on dyads and other interdependent groups. The book is essential for those planning to study development in dyadic or group relationships. As the authors cogently argue, to fail to account for change in the study of relationships is to misunderstand relationships, while the failure to account for relationships in the study of change just as reliably results in a failure to understand change. Thus, the book positions itself to guide researchers in a direction essential for the field of developmental psychology." - Clifton R. Emery, PsycCRITIQUES

• N.A. Card, T.D. Little, J.P. Selig, Modeling Dyadic and Interdependent Data in Developmental Research: An Introduction. B. Laursen, D. Popp, W.J. Burk, M. Kerr, H. Stattin, Incorporating Interdependence into Developmental Research: Examples from the Study of Homophily and Homogeneity. W.L. Cook, Application of the Social Relations Model Formulas to Developmental Research. A.H.N. Cillessen, C. Borch, Analyzing Social Networks in Adolescence. N. Ram, A.B. Pedersen, Dyadic Models Emerging from the Longitudinal Structural Equation Modeling Tradition: Parallels with Ecological Models of Interspecific Interactions. E. Ferrer, K.F. Widaman, Multilevel Structural Equation Models for Contextual Factors with Inter-Group Differences. P. Sadler, E. Woody, It Takes Two: A Dyadic, SEM-Based Perspective on Personality Development. D.A. Kashy, M.B. Donnellan, Comparing MLM and SEM Approaches to Analyzing Developmental Dyadic Data: Growth Curve Models of Hostility in Families. J.P. Selig, K.A. McNamara, N.A. Card, T.D. Little, Techniques for Modeling Dependency in Interchangeable Dyads. T.E. Malloy, A.H.N. Cillessen, Variance Component Analysis of Generalized and Dyadic Peer Perceptions in Adolescence. N.A. Card, T.D. Little, J.P. Selig, Using the Bivariate Social Relations Model to Study Dyadic Relationships: Early Adolescents’ Perceptions of Friends’ Aggression and Prosocial Behavior. S.J.T. Branje, C. Finkenauer, W.H.J. Meeus, Modeling Interdependence Using the Social Relations Model: The Investment Model in Family Relationships. J. Templin, Methods for Detecting Subgroups in Social Networks. T.A. Kindermann, Can We Use Causal Inferences about the Influence of Children's Naturally-Existing Social Networks on their School Motivation? B.J.H. Zijlstra, R. Veenstra, M.A.J. Van Duijn, An Application of the Multilevel Model for Binary Network Data on Bully-Victim Relationships. C.F. Bond, Jr., D. Cross, Beyond the Dyad: Prospects for Social Development. D.A. Kenny, Thinking about the Developmental Course of Relationships.