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Modeling and Predicting Complex Patterns of Change Using Growth Component Models: An Application to Depression Trajectories in Cancer Patients
October 2019 • Axel Mayer, Christian Geiser, Frank J. Infurna, Christiane Fiege
In this paper, we present a general and flexible framework for constructively defining growth components to model complex change processes. Building on the concepts of the latent state-trait theory (LST theory; Steyer, Ferring, & Schmitt, 1992), we develop structural equation models containing latent variables that represent latent growth (change) components of interest. We formulate these models based on an approach presented by Mayer, Steyer & Mueller (in press). We discuss an application to the …