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ERIC Number: EJ725008
Record Type: Journal
Publication Date: 2005
Pages: 17
Abstractor: Author
ISBN: N/A
ISSN: ISSN-1070-5511
The Biasing Effects of Unmodeled ARMA Time Series Processes on Latent Growth Curve Model Estimates
Sivo, Stephen; Fan, Xitao; Witta, Lea
Structural Equation Modeling: A Multidisciplinary Journal, v12 n2 p215-231 2005
The purpose of this study was to evaluate the robustness of estimated growth curve models when there is stationary autocorrelation among manifest variable errors. The results suggest that when, in practice, growth curve models are fitted to longitudinal data, alternative rival hypotheses to consider would include growth models that also specify autoregressive (AR), moving average (MA), and autoregressive moving average (ARMA) processes. AR (i.e., simplex) processes are commonly found in longitudinal data and may diminish the ability of a researcher to detect growth if not explicitly modeled. MA and ARMA processes do not affect the fit of growth models, but do notably bias some of the parameters.
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.
Publication Type: Journal Articles; Reports - Evaluative
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A