Growth mixture modeling with non-normal distributions
Growth mixture modeling with non-normal distributions
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DOI：
10.1002/sim.6388
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发表时间：
2015-03-15
影响因子：
2
通讯作者：
Asparouhov, Tihomir
中科院分区：
文献类型：
--
作者：
Muthen, Bengt;Asparouhov, Tihomir
以前的工作增长混合建模的一个限制性特征是假设每个潜在类内的正态分布变量。对于强非正态结果，这意味着需要几个潜在类来捕获观察到的变量分布。能够放松类内正态性假设的优点是，观察到的非正态分布不需要使用多个类来拟合分布。添加表示尾部偏斜度和厚度的参数是有价值的。一个新的增长混合模型，这种提出了借鉴最近的工作中的一系列文件，使用偏t分布。新的方法说明了使用纵向发展的身体质量指数在两个数据集。第一组数据来自全国青年纵向调查，涵盖12-23岁。在这里，发展与先行测量的社会经济背景。第二个数据集来自心脏病研究，覆盖年龄25-65岁。在此，使用联合生长混合生存模型，该发展与高血压治疗的并发事件相关。版权所有（C）2014约翰威利父子有限公司
A limiting feature of previous work on growth mixture modeling is the assumption of normally distributed variables within each latent class. With strongly non-normal outcomes, this means that several latent classes are required to capture the observed variable distributions. Being able to relax the assumption of within-class normality has the advantage that a non-normal observed distribution does not necessitate using more than one class to fit the distribution. It is valuable to add parameters representing the skewness and the thickness of the tails. A new growth mixture model of this kind is proposed drawing on recent work in a series of papers using the skew-t distribution. The new method is illustrated using the longitudinal development of body mass index in two data sets. The first data set is from the National Longitudinal Survey of Youth covering ages 12-23 years. Here, the development is related to an antecedent measuring socioeconomic background. The second data set is from the Framingham Heart Study covering ages 25-65 years. Here, the development is related to the concurrent event of treatment for hypertension using a joint growth mixture-survival model. Copyright (C) 2014 John Wiley & Sons, Ltd.