On Fitting a Multivariate Two-Part Latent Growth Model

被引：9

作者：

Xu, Shu ^{[1
]}

Blozis, Shelley A. ^{[2
]}

Vandewater, Elizabeth A. ^{[3
]}

机构：

[1] NYU, New York, NY 10003 USA

[2] Univ Calif Davis, Davis, CA 95616 USA

[3] Univ Texas Austin, Austin, TX 78712 USA

来源：

STRUCTURAL EQUATION MODELING-A MULTIDISCIPLINARY JOURNAL | 2014年 / 21卷 / 01期

关键词：

longitudinal semicontinuous variables; Monte Carlo integration; multivariate two-part latent growth curve model; PARTICIPATION; TRAJECTORIES; CHILDREN;

D O I：

10.1080/10705511.2014.856699

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

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 Mplus 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.

引用

页码：131 / 148

页数：18