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Dyadic longitudinal models: A critical review
Authors:Masumi Iida  Andrea Savord  Thomas Ledermann
Affiliation:1. School of Social and Family Dynamics, Arizona State University, Tempe, Arizona, USA;2. Department of Psychology, Arizona State University, Tempe, Arizona, USA;3. Department of Human Development and Family Science, Florida State University, Tallahassee, Florida, USA
Abstract:In this review, we discuss the most commonly used models to analyze dyadic longitudinal data. We start the review with a definition of dyadic longitudinal data that allows relationship researchers to identify when these models might be appropriate. Then, we go on to describe the three major models commonly used when one has dyadic longitudinal data: the dyadic growth curve model (DGCM), the actor–partner interdependence model (APIM), and the common fate growth model (CFGM). We discuss when each model might be used and strengths and weaknesses of each model. We end with additional thoughts that focus on extensions to new methods being discussed in the literature, along with some of the challenges of collecting and analyzing dyadic longitudinal data that might be helpful for future dyadic researchers.
Keywords:actor–partner interdependence models  common fate growth modeling  dyadic growth curve model  longitudinal dyadic data analysis  multilevel modeling  structural equation modeling
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