Piecewise modeling for longitudinal psychological research: a tutorial using R
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Updated: Nov 7, 2026

Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills
Published on: September 17, 2019
1Department of Psychology, Chungbuk National University, Cheongju, Chungbuk, Republic of Korea.
Abstract:
Longitudinal psychological research often centers on key developmental transitions, where patterns of change may differ across stages. Piecewise modeling is well suited to capturing these stage-specific changes. This tutorial introduces three piecewise methods in longitudinal psychological research: piecewise multilevel modeling (MLM), piecewise latent class growth modeling (LCGM), and latent transition analysis (LTA). Drawing on a six-wave longitudinal study of national identity development, we show how each method can be implemented in R and highlight the types of research questions each is designed to address, from estimating average developmental trajectories to identifying heterogeneous trajectory patterns and examining transitions between latent developmental states.
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