Finite mixture modeling with mixture outcomes using the EM algorithm
Finite mixture modeling with mixture outcomes using the EM algorithm
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DOI：
10.1111/j.0006-341x.1999.00463.x
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发表时间：
1999-06-01
期刊：
影响因子：
1.9
通讯作者：
Shedden, K
中科院分区：
文献类型：
--
作者：
Muthén, B;Shedden, K
本文讨论了扩展有限混合模型的分析，其中一组观测变量的混合成分对应的潜在类影响第二组观测变量。该研究的动机是一个重复测量研究，使用随机系数模型来评估潜在的增长轨迹类成员的影响，一个二元疾病的结果的概率。更一般地，该模型可以被视为潜在类建模和传统混合建模的组合。EM算法用于估计。作为一个例子，一个随机系数的增长模型预测酒精依赖的三个潜在类的沉重的酒精使用轨迹的年轻人进行了分析。
This paper discusses the analysis of an extended finite mixture model where the latent classes corresponding to the mixture components for one set of observed variables influence a second set of observed variables. The research is motivated by a repeated measurement study using a random coefficient model to assess the influence of latent growth trajectory class membership on the probability of a binary disease outcome. More generally, this model can be seen as a combination of latent class modeling and conventional mixture modeling. The EM algorithm is used for estimation. As an illustration, a random-coefficient growth model for the prediction of alcohol dependence from three latent classes of heavy alcohol use trajectories among young adults is analyzed.