ERIC Number: EJ1019153
Record Type: Journal
Publication Date: 2013-Dec
Abstractor: As Provided
Reference Count: 37
Sample Size Requirements for Structural Equation Models: An Evaluation of Power, Bias, and Solution Propriety
Wolf, Erika J.; Harrington, Kelly M.; Clark, Shaunna L.; Miller, Mark W.
Educational and Psychological Measurement, v73 n6 p913-934 Dec 2013
Determining sample size requirements for structural equation modeling (SEM) is a challenge often faced by investigators, peer reviewers, and grant writers. Recent years have seen a large increase in SEMs in the behavioral science literature, but consideration of sample size requirements for applied SEMs often relies on outdated rules-of-thumb. This study used Monte Carlo data simulation techniques to evaluate sample size requirements for common applied SEMs. Across a series of simulations, we systematically varied key model properties, including number of indicators and factors, magnitude of factor loadings and path coefficients, and amount of missing data. We investigated how changes in these parameters affected sample size requirements with respect to statistical power, bias in the parameter estimates, and overall solution propriety. Results revealed a range of sample size requirements (i.e., from 30 to 460 cases), meaningful patterns of association between parameters and sample size, and highlight the limitations of commonly cited rules-of-thumb. The broad "lessons learned" for determining SEM sample size requirements are discussed.
Descriptors: Sample Size, Structural Equation Models, Statistical Analysis, Statistical Bias, Monte Carlo Methods, Factor Analysis
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Publication Type: Reports - Research; Journal Articles
Education Level: N/A
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