Definition
Latent growth curve models (LGMs) are a popular approach for the analysis of change by means of structural equation models (SEM). Typically, LGMs are used for the analysis of panel data with many subjects (N large) and few time points (Tsmall). Often, the parameters of a polynomial growth function of time (or a proxy of time, such as age or measurement occasion) are estimated, although nonpolynomial growth curves are possible as well. Individual differences are represented by latent variables, corresponding to random effects in linear mixed models. Similar to linear mixed models, time-varying and time-invariant predictors may be included to explain changes in growth trajectories and individual differences therein. Drawing upon the flexibility of the (extended) SEM framework, LGMs take advantage of the usual SEM assets, including the possibility of a graphical...
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Voelkle, M.C. (2020). Latent Growth Curve Models (LGMs). In: Zeigler-Hill, V., Shackelford, T.K. (eds) Encyclopedia of Personality and Individual Differences. Springer, Cham. https://doi.org/10.1007/978-3-319-24612-3_1320
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