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.
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