Mixture Latent Markov Modeling: Identifying and Predicting Unobserved Heterogeneity in Longitudinal Qualitative Status Change
用退休后就业状态的真实数据，演示混合潜在马尔可夫模型如何识别纵向定性变化中的群体差异，并分析其影响因素，适合组织研究者判断是否采用该方法。
There are many areas of organizational research where we may be concerned with subgroup differences in status change profiles. The purpose of this article is to illustrate, using a real data set on retirees’ postretirement employment statuses (PES), how mixture latent Markov modeling may be applied to substantive research in organizational settings to identify population subgroups with varying status change profiles and examine their correlates, by modeling unobserved heterogeneity in longitudinal qualitative changes. Steps in the modeling process are highlighted and limitations, cautions, recommendations, and extensions of the technique are discussed.