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.

中文翻译：

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距离和形状对分段增长混合模型估计的影响

分段增长混合模型用于纵向研究，以复合方式处理非连续轨迹和未观察到的异质性。本研究调查了潜在距离和形状等因素如何影响模型。使用两个模拟研究来探索以样本大小、潜在距离（Mahalanobis 距离）和形状作为影响因素的 2 类和 3 类情况。两次模拟的结果表明，非平行形状导致整体模型拟合稍好。参数估计受形状影响，主要是通过潜在类之间的参数差异。