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A Note on Structural Equation Modeling Estimates of Reliability
- Source :
- Structural Equation Modeling: A Multidisciplinary Journal. 17:66-81
- Publication Year :
- 2010
- Publisher :
- Informa UK Limited, 2010.
-
Abstract
- Reliability can be estimated using structural equation modeling (SEM). Two potential problems with this approach are that estimates may be unstable with small sample sizes and biased with misspecified models. A Monte Carlo study was conducted to investigate the quality of SEM estimates of reliability by themselves and relative to coefficient alpha. The SEM approach showed minimal bias when the model was correctly specified if items were relatively well defined by their underlying factor(s). They tended to demonstrate somewhat greater bias when the model was misspecified, particularly underspecified. Overall, SEM estimates were more stable than anticipated. Researchers are more likely to obtain accurate estimates of reliability using SEM by conducting large-sample studies with well-constructed scales and critically assessing model fit.
- Subjects :
- Sociology and Political Science
Item analysis
Monte Carlo method
General Decision Sciences
Small sample
Structural equation modeling
Cronbach's alpha
Goodness of fit
Sample size determination
Modeling and Simulation
Statistics
Econometrics
General Economics, Econometrics and Finance
Reliability (statistics)
Mathematics
Subjects
Details
- ISSN :
- 15328007 and 10705511
- Volume :
- 17
- Database :
- OpenAIRE
- Journal :
- Structural Equation Modeling: A Multidisciplinary Journal
- Accession number :
- edsair.doi...........9d96d73606474e33482ddef09bc1ee83
- Full Text :
- https://doi.org/10.1080/10705510903438963