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Effects of Distance and Shape on the Estimation of the Piecewise Growth Mixture Model

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An Erratum to this article was published on 31 May 2019

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Abstract

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.

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  • 31 May 2019

    The authors missed an important reference “Liu, Luo, & Liu, 2014” on the original version of this article.

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Funding

National Natural Science Foundation of China (No. 31800950, No. 31571152).

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Correspondence to Hongyun Liu.

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Liu, Y., Liu, H. Effects of Distance and Shape on the Estimation of the Piecewise Growth Mixture Model. J Classif 36, 659–677 (2019). https://doi.org/10.1007/s00357-018-9291-9

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  • DOI: https://doi.org/10.1007/s00357-018-9291-9

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