Effects of distance and shape on the estimation of the piecewise growth mixture model. (English) Zbl 1436.62274

Liu, Yuan; Liu, Hongyun

J. Classif. 36, No. 3, 659-677 (2019); erratum ibid. 36, No. 3, 678 (2019).

Summary: The piecewise growth mixture model is used in longitudinal studies to tackle non-continuous trajectories and unobserved heterogeneity in a compound way. This study investigated how factors such as latent distance and shape influence the model. Two simulation studies were used exploring the 2- and 3-class situation with sample size, latent distance (Mahalanobis distance), and shape being considered as the influencing factor. The results of two simulations showed that a non-parallel shape led to a slightly better overall model fit. Parameter estimation is affected by the shape, mainly through the parameter differences between latent classes.

MSC:

62H30	Classification and discrimination; cluster analysis (statistical aspects)
62H11	Directional data; spatial statistics

Keywords:

piecewise growth mixture model (PGMM); latent distance; shape; parameter difference

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