ISSN : 1229-067X
The mediational model is one of the most actively used analytical methods in the social sciences or psychology. However, the methods of testing the mediated effect with categorical dependent variables have been relatively unknown. The aims of the present study are to integrate studies on the methods of estimating the mediated effect of the model with a binary dependent variable over the last 30 years and to discuss key issues in order to encourage researchers to choose the most appropriate approach to their data. To achieve this goal, we explore the two streams of estimating the mediated effect of the model with a binary dependent variable, traditional vs. causal inference approaches. For the traditional approach,we introduce and integrate several extended structural equation modeling methods that accommodate a binary dependent variable in the mediational model. Then, we introduce the causal inference approach which allows researchers to estimate the mediated effect non-parametrically without specifying the form or distribution of the model before estimation, and extend it into a model that includes a binary dependent variable. Finally, we illustrate the procedures for applying the traditional and the causal inference approaches using real data and discuss the results.
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