Modeling latent growth curves with incomplete data using different types of structural equation modeling and multilevel software

被引:73
作者
Ferrer, E
Hamagami, F
McArdle, JJ
机构
[1] Univ Calif Davis, Dept Psychol, Davis, CA 95616 USA
[2] Univ Virginia, Dept Psychol, Charlottesville, VA 22903 USA
关键词
D O I
10.1207/s15328007sem1103_8
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
This article offers different examples of how to fit latent growth curve (LGC) models to longitudinal data using a variety of different software programs (i.e., LISREL, Mx, Mplus, AMOS, SAS). The article shows how the same model can be fitted using both structural equation modeling and multilevel software, with nearly identical results, even in the case of models of latent growth fitted to incomplete data. The general purpose of this article is to provide a demonstration that integrates programming features from different software. The most immediate goal is to help researchers implement these LGC models as a useful way to test hypotheses of growth.
引用
收藏
页码:452 / 483
页数:32
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