Modeling latent growth curves with incomplete data using different types of structural equation modeling and multilevel software
Modeling latent growth curves with incomplete data using different types of structural equation modeling and multilevel software
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DOI：
10.1207/s15328007sem1103_8
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发表时间：
2004-01-01
影响因子：
6
通讯作者：
McArdle, JJ
中科院分区：
文献类型：
--
作者：
Ferrer, E;Hamagami, F;McArdle, JJ
本文提供了如何使用各种不同的软件程序（即，LISREL、Mx、Mplus、AMOS、SAS）。本文展示了如何使用结构方程模型和多层次软件来拟合相同的模型，即使是在拟合不完整数据的潜在增长模型的情况下，结果也几乎相同。本文的总体目的是提供一个集成不同软件的编程特性的演示。最直接的目标是帮助研究人员实施这些LGC模型，作为检验增长假设的有用方法。
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.