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Monte Carlo Methods2
Structural Equation Models2
Comparative Analysis1
Error of Measurement1
Estimation (Mathematics)1
Maximum Likelihood Statistics1
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Structural Equation Modeling2
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Bandalos, Deborah L.2
Enders, Craig K.1
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The Relative Performance of Full Information Maximum Likelihood Estimation for Missing Data in Structural Equation Models.
Peer reviewed Peer reviewed
Enders, Craig K.; Bandalos, Deborah L. – Structural Equation Modeling, 2001
Used Monte Carlo simulation to examine the performance of four missing data methods in structural equation models: (1)full information maximum likelihood (FIML); (2) listwise deletion; (3) pairwise deletion; and (4) similar response pattern imputation. Results show that FIML estimation is superior across all conditions of the design. (SLD)
Descriptors: Maximum Likelihood Statistics, Monte Carlo Methods, Simulation, Structural Equation Models
Assessing Sources of Error in Structural Equation Models: The Effects of Sample Size, Reliability, and Model Misspecification.
Peer reviewed Peer reviewed
Bandalos, Deborah L. – Structural Equation Modeling, 1997
Monte Carlo methods were used to study the accuracy and utility of estimators of overall error and error due to approximation in structural equation modeling. Effects of sample size, indicator reliabilities, and degree of misspecification were examined. The rescaled noncentrality parameter also was examined. Choosing among competing models is…
Descriptors: Comparative Analysis, Error of Measurement, Estimation (Mathematics), Monte Carlo Methods