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ERIC Number: ED464125
Record Type: Non-Journal
Publication Date: 2002-Apr
Pages: 36
Abstractor: N/A
Reference Count: N/A
ISBN: N/A
ISSN: N/A
Power of Latent Growth Modeling for Detecting Group Differences in Linear Growth Trajectory Parameters.
Fan, Xitao
This simulation study focused on the power of detecting group differences in linear growth trajectory parameters within the framework of structural equation modeling (SEM) and compared this approach with the more traditional repeated measures analysis of variance (ANOVA) approach. Three broad conditions of group differences in linear growth trajectory were considered. SEM latent growth modeling consistently showed higher statistical power for detecting group differences in the linear growth slopes than repeated measures ANOVA. For small group differences in the growth trajectories, large sample size (e.g., N>500) is typically required for adequate statistical power. For medium or large group differences, moderate or small sample size is usually sufficient for adequate power. Some future research directions are discussed. (Contains 2 figures, 8 tables, and 16 references.) (Author/SLD)
Publication Type: Reports - Research; Speeches/Meeting Papers
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A