Structural equation modeling with ordinal variables: a large sample case study

Abstract

In the behavioral sciences, response variables are often non-continuous, ordinal variables. Conventional structural equation models (SEMs) have been generalized to accommodate ordinal responses. In this study, three different estimation methods on real data were performed with ordinal variables. Empirical results obtained from the different estimation methods on given real large sample educational data were investigated and compared to recent simulation results. As a result, even very large sample is available, model estimations and fits for ordinal data are affected from inconvenient estimation methods thus it is concluded that asymptotically distribution free estimation method specialized for ordinal variables is more convenient way to model ordinal variables.