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Modeling Dyadic and Interdependent Data in the Developmental and Behavioral Sciences

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actor
Actor Partner Interdependence Model
actor partner model
adolescent social networks
advanced statistical modeling
APIM Analysis
Category=GPS
Category=JB
Category=JHB
Category=JMA
Category=JMB
Category=JNM
Clique Membership
Data Set
design
Dyad Members
Dyadic Covariates
Dyadic Data
dyadic data analysis
Dyadic Reciprocity
effects
eq_bestseller
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_society-politics
Growth Curve Models
Indistinguishable Dyads
Interchangeable Dyads
interdependence
Interdependent Data
Investment Model Variables
Latent Difference Score Model
Latent Variables
longitudinal dyadic research methods
members
Mutual Influence Model
Overt Aggression
PANAS Item
partner
Partner Effect
Partner Variance
peer influence measurement
Peer Perceptions
Perceiver Effect
Relational Aggression
relations
robin
round
Round Robin Design
social
Social Relations Model
social relations theory

Product details

  • ISBN 9780805859720
  • Weight: 725g
  • Dimensions: 152 x 229mm
  • Publication Date: 09 Jul 2008
  • Publisher: Taylor & Francis Inc
  • Publication City/Country: US
  • Product Form: Hardback
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Description

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 addresses:

  • 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.
About
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.