An Introduction and Integration of Cross-Classified, Multiple Membership, and Dynamic Group Random-Effects Models

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Abstract

In longitudinal studies, time-varying group membership and group effects are important issues that need to be addressed. In this article we describe use of cross-classified and multiple membership random-effects models to address time-varying group membership, and dynamic group random-effects models to address time-varying group effects. We propose new models that integrate features of existing models, evaluate these models through simulation, provide guidance on how to fit these models, and apply the models in 2 real data examples. The discussion focuses on challenges in the application of these models.

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