关于拟合多元两部分潜在增长模型
On Fitting a Multivariate Two-Part Latent Growth Model.
作者信息
Xu Shu, Blozis Shelley A, Vandewater Elizabeth A
机构信息
New York University.
University of California, Davis.
出版信息
Struct Equ Modeling. 2014;21(1):131-148. doi: 10.1080/10705511.2014.856699. Epub 2014 Jan 31.
A 2-part latent growth model can be used to analyze semicontinuous data to simultaneously study change in the probability that an individual engages in a behavior, and if engaged, change in the behavior. This article uses a Monte Carlo (MC) integration algorithm to study the interrelationships between the growth factors of 2 variables measured longitudinally where each variable can follow a 2-part latent growth model. A SAS macro implementing M is developed to estimate the model to take into account the sampling uncertainty of this simulation-based computational approach. A sample of time-use data is used to show how maximum likelihood estimates can be obtained using a rectangular numerical integration method and an MC integration method.
两部分潜在增长模型可用于分析半连续数据，以同时研究个体参与某种行为的概率变化，以及若参与该行为，行为本身的变化。本文使用蒙特卡罗（MC）积分算法来研究纵向测量的两个变量的增长因素之间的相互关系，其中每个变量都可以遵循两部分潜在增长模型。开发了一个实现MC的SAS宏来估计模型，以考虑这种基于模拟的计算方法的抽样不确定性。使用一个时间使用数据样本来说明如何使用矩形数值积分法和MC积分法获得最大似然估计。
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