Review of Growth Modeling: Structural Equation and Multilevel Modeling Approaches (Grimm, Ram & Estabrook, 2017)

Maxwell R. Hong () and Ross Jacobucci
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Maxwell R. Hong: University of Notre Dame
Ross Jacobucci: University of Notre Dame

Psychometrika, 2019, vol. 84, issue 1, No 17, 327-332

Abstract: Abstract Research questions that address developmental processes are becoming more prevalent in psychology and other areas of social science. Growth models have become a popular tool to model multiple individuals measured over several time points. These types of models allow researchers to answer a wide variety of research questions, such as modeling inter- and intra-individual differences and variability in longitudinal process (Molenaar 2004). The recently published book, Growth Modeling: Structural Equation and Multilevel Modeling Approaches (Grimm, Ram & Estabrook 2017), provides a solid foundation for both beginners and more advanced researchers interested in longitudinal data analysis by juxtaposing both the multilevel and structural equation modeling frameworks for several different models. By providing both sufficient technical background and practical coding examples in a variety of both commercial and open-source software, this book should serve as an excellent reference tool for behavioral and methodological researchers interested in growth modeling.

Keywords: growth modeling; structural equation modeling; multilevel modeling; longitudinal research (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1007/s11336-018-9634-9

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