An introduction to growth mixture models (GMM)

Tae Kyoung Lee; Kandauda A.S. Wickrama; Catherine Walker O'Neal

doi:10.1016/B978-0-12-818630-5.10076-4

An introduction to growth mixture models (GMM)

Tae Kyoung Lee, Kandauda A.S. Wickrama, Catherine Walker O'Neal

Department of Child Psychology and Education

University of Georgia

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

Abstract

Popular research methods addressing change over time often fail to consider the heterogeneity that may exist in trajectories over time. Building on a latent growth curve model in a structural equation framework, with longitudinal data over multiple time points, possible heterogeneity trajectories can be investigated with growth mixture modeling. We begin by introducing latent growth models then describe how they can be extended to account for different trajectories across multiple latent classes. A step-by-step illustration using Mplus software is presented to show how this model can be applied in practice. Program syntax is provided.

Original language	English
Title of host publication	International Encyclopedia of Education
Subtitle of host publication	Fourth Edition
Publisher	Elsevier
Pages	646-656
Number of pages	11
ISBN (Electronic)	9780128186299
DOIs	https://doi.org/10.1016/B978-0-12-818630-5.10076-4
State	Published - 1 Jan 2022

Keywords

Growth mixture model
Latent class growth analysis
Latent growth model
Longitudinal studies
Mental health
Mplus

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10.1016/B978-0-12-818630-5.10076-4

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BT - International Encyclopedia of Education

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ER -

An introduction to growth mixture models (GMM)

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Keywords

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