Modeling Latent Growth Curves With Incomplete Data Using Different Types of Structural Equation Modeling and Multilevel Software

Autor/inn/en	Ferrer, Emilio; Hamagami, Fumiaki; McArdle, John J.
Titel	Modeling Latent Growth Curves With Incomplete Data Using Different Types of Structural Equation Modeling and Multilevel Software
Quelle	In: Structural Equation Modeling, 11 (2004) 3, S.452-483 (32 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1070-5511
Schlagwörter	Computer Software; Structural Equation Models; Longitudinal Studies; Data Analysis; Hypothesis Testing; Evaluation Methods + Suchen Sie Ihr Suchwort? Longitudinal study; Longitudinal method; Longitudinal methods; Längsschnittuntersuchung; Auswertung; Hypothesenprüfung; Hypothesentest
Abstract	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. (Author).
Anmerkungen	Lawrence Erlbaum Associates, Inc., Journal Subscription Department, 10 Industrial Avenue, Mahwah, NJ 07430-2262. Tel: 800-926-6579 (Toll Free); e-mail: journals@erlbaum.com.
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10