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“How Well Does Your Structural Equation Model Fit Your Data?”: Is Marcoulides And Yuan’S Equivalence Test The Answer?, James Peugh, David F. Feldon

Instructional Technology and Learning Sciences Faculty Publications

Structural equation modeling is an ideal data analytical tool for testing complex relationships among many analytical variables. It can simultaneously test multiple mediating and moderating relationships, estimate latent variables on the basis of related measures, and address practical issues such as nonnormality and missing data. To test the extent to which a hypothesized model provides an appropriate characterization of the collective relationships among its variables, researchers must assess the “fit” between the model and the sample’s data. However, interpreting estimates of model fit is a problematic process. The traditional inferential test of model fit, the chi-square test, is biased due …