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Physical Sciences and Mathematics Commons™
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Articles 1 - 3 of 3
Full-Text Articles in Physical Sciences and Mathematics
Impact Of Measurement Model Modification On Structural Parameter Integrity When Measurement Model Is Misspecified, Weihua Fan
Journal of Modern Applied Statistical Methods
In the process of model modification, parameters of residual covariances are often treated as free parameters to improve model fit. However, the effect of such measurement model modifications on the important structural parameter estimates under various measurement model misspecifications has not been systematically studied. Monte Carlo simulation was conducted to compare structural estimates before and after measurement model modifications of adding residual covariances under varying sample sizes and model misspecifications. Results showed that researchers should pay attention when such measurement model modifications are made to initially misspecified model with missing path(s).
An Evaluation Of Multiple Imputation For Meta-Analytic Structural Equation Modeling, Carolyn F. Furlow, S. Natasha Beretvas
An Evaluation Of Multiple Imputation For Meta-Analytic Structural Equation Modeling, Carolyn F. Furlow, S. Natasha Beretvas
Journal of Modern Applied Statistical Methods
A simulation study was used to evaluate multiple imputation (MI) to handle MCAR correlations in the first step of meta-analytic structural equation modeling: the synthesis of the correlation matrix and the test of homogeneity. No substantial parameter bias resulted from using MI. Although some SE bias was found for meta-analyses involving smaller numbers of studies, the homogeneity test was never rejected when using MI.
Can Specification Searches Be Useful For Hypothesis Generation?, Samuel B. Green, Marilyn S. Thompson
Can Specification Searches Be Useful For Hypothesis Generation?, Samuel B. Green, Marilyn S. Thompson
Journal of Modern Applied Statistical Methods
Previous studies suggest that results from specification searches, as typically employed in structural equation modeling, should not be used to reach strong research conclusions due to their poor reliability. Analyses of computer generated data indicate that search results can be sufficiently reliable for exploratory purposes with properly designed and analyzed studies.