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Social and Behavioral Sciences Commons™
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Full-Text Articles in Social and Behavioral Sciences
Limitations In The Systematic Analysis Of Structural Equation Model Fit Indices, Sarah A. Rose, Barry Markman, Shlomo Sawilowsky
Limitations In The Systematic Analysis Of Structural Equation Model Fit Indices, Sarah A. Rose, Barry Markman, Shlomo Sawilowsky
Journal of Modern Applied Statistical Methods
The purpose of this study was to evaluate the sensitivity of selected fit index statistics in determining model fit in structural equation modeling (SEM). The results indicated a large dependency on correlation magnitude of the input correlation matrix, with mixed results when the correlation magnitudes were low and a primary indication of good model fit. This was due to the default SEM method of Maximum Likelihood that assumes unstandardized correlation values. However, this warning is not well-known, and is only obscurely mentioned in some textbooks. Many SEM computer software programs do not give appropriate error indications that the results are …
Jmasm40: Monte Carlo Simulations For Structural Equation Modelling (Revolution R), Sarah A. Rose, Barry Markman
Jmasm40: Monte Carlo Simulations For Structural Equation Modelling (Revolution R), Sarah A. Rose, Barry Markman
Journal of Modern Applied Statistical Methods
Revolution R code is presented to setup Structural Equation Model (SEM) for a Monte Carlo study. The example is a comparison of different fit indices.
The Not-So-Quiet Revolution: Cautionary Comments On The Rejection Of Hypothesis Testing In Favor Of A “Causal” Modeling Alternative, Daniel H. Robinson, Joel R. Levin
The Not-So-Quiet Revolution: Cautionary Comments On The Rejection Of Hypothesis Testing In Favor Of A “Causal” Modeling Alternative, Daniel H. Robinson, Joel R. Levin
Journal of Modern Applied Statistical Methods
Rodgers (2010) recently applauded a revolution involving the increased use of statistical modeling techniques. It is argued that such use may have a downside, citing empirical evidence in educational psychology that modeling techniques are often applied in cross-sectional, correlational studies to produce unjustified causal conclusions and prescriptive statements.