MODELING INCOMPLETE LONGITUDINAL AND CROSS-SECTIONAL DATA USING LATENT GROWTH STRUCTURAL MODELS

被引：147
|
作者：
MCARDLE, JJ
HAMAGAMI, F
机构：
来源：
EXPERIMENTAL AGING RESEARCH | 1992年 / 18卷 / 3-4期
关键词：
D O I：
10.1080/03610739208253917
中图分类号：
R592 [老年病学]; C [社会科学总论];
学科分类号：
03 ; 0303 ; 100203 ;
摘要：
In this paper we describe some mathematical and statistical models for identifying and dealing with changes over age. We concentrate specifically on the use of a latent growth structural equation model approach to deal with issues of: (1) latent growth models of change, (2) differences in longitudinal and cross-sectional results, and (3) differences due to longitudinal attrition. This is a methodological paper using simulated data, but we base our models on practical and conceptual principles of modeling change in developmental psychology. Our results illustrate both benefits and limitations using structural models to analyze incomplete longitudinal data.
引用
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页码：145 / 166
页数：22
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