Modeling Contextual Effects in Longitudinal Studies
Todd D. Little • James A. Bovaird • Noel A. Card

Longitudinal data are critical for understanding how individuals change across time. Researchers are faced with a complex task when modeling the contexts in which longitudinal processes unfold. Modeling Contextual Effects in Longitudinal Studies reviews the challenges and alternative approaches to modeling these influences and provides methodologies and data analytic strategies for behavioral and social science researchers.

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Modeling Dyadic and Interdependent Data in the
Developmental and Behavioral Sciences
Noel A. Card • James P. Selig • Todd D. Little

Text in preperation for publishing...
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Latent Growth Curve Modeling
Kristopher J. Preacher • Aaron L. Wichman • Robert C. MacCallum
Nancy E. Briggs

Latent growth curve modeling (LGM), a special case of confirmatory factor analysis designed to model change over time, is an indispensable tool for modeling longitudinal data. This volume introduces LGM techniques to researchers, provides easy-to-follow, didactic examples of several common growth modeling approaches, and highlights recent advances regarding the treatment of missing data, parameter estimation, and model fit.

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