Abstract
Factorial invariance assessment is central in the development of educational and psychological assessments. Establishing invariance of factor structures is key for building a strong score and inference validity argument and assists in establishing the fairness of score use. Fit indices and guidelines for judging a lack of invariance is an ongoing line of research. In this study, the authors examined the performance of the root mean squared error of approximation equivalence testing approach described by Yuan and Chan in the context of measurement invariance assessment. This investigation was completed through a simulation study in which several factors were varied, including sample size, type of invariance tested, and magnitude and percent of a lack of invariance. The findings generally support the use of equivalence testing for situations in which the indicator variables were normally distributed, particularly for total sample sizes of 200 or more.
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