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Schumacker, Randall E.; Cheevatanarak, Suchittra – 2000
Monte Carlo simulation compared chi-square statistics, parameter estimates, and root mean square error of approximation values using normal and elliptical estimation methods. Three research conditions were imposed on the simulated data: sample size, population contamination percent, and kurtosis. A Bentler-Weeks structural model established the…
Descriptors: Chi Square, Comparative Analysis, Estimation (Mathematics), Monte Carlo Methods
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
Peer reviewed Peer reviewed
Moulder, Bradley C.; Algina, James – Structural Equation Modeling, 2002
Used simulation to compare structural equation modeling methods for estimating and testing hypotheses about an interaction between continuous variables. Findings indicate that the two-stage least squares procedure exhibited more bias and lower power than the other methods. The Jaccard-Wan procedure (J. Jaccard and C. Wan, 1995) and maximum…
Descriptors: Comparative Analysis, Estimation (Mathematics), Hypothesis Testing, Least Squares Statistics
Schumacker, Randall E. – 1992
Several goodness of fit (GOF) criteria have been developed to assist the researcher in interpreting structural equation models. However, the determination of GOF for structural equation models is not as straightforward as that for other statistical approaches in multivariate procedures. The four GOF criteria used across the commonly used…
Descriptors: Chi Square, Comparative Analysis, Equations (Mathematics), Estimation (Mathematics)