Mediation is a hypothesized causal chain among three variables. Mediation analysis for continuous response variables is well developed in the literature, and it can be shown that the indirect effect is equal to the total effect minus the direct effect. However, mediation analysis for categorical responses is still not fully developed. The purpose of this article is to propose a simpler method of analysing the mediation effect among three variables when the dependent and mediator variables are both dichotomous. he researchers propose using the latent variable technique which in turn will adjust for the necessary condition that indirect effect is equal to the total effect minus the direct effect. An intensive simulation study is conducted to compare the proposed method with other methods in the literature. The researchers’ theoretical derivation and simulation study show that the proposed approach is simpler to use and at least as good as other approaches provided in the literature. They illustrate their approach to test for the potential mediators on the relationship between depression and obesity among children and adolescents compared to the method in Winship and Mare using National children health survey data 2011 – 2012.
“A simpler approach for mediation analysis for dichotomous mediators in logistic regression,” was recently published in the Journal of Statistical Computation and Simulation.
Georgia Southern University Jiann-Ping Hsu College of Public Health biostatistics faculty, Dr. Hani Samawi, lead author, Dr. Jingxian Cai, Dr. Daniel F. Linder (former), Dr. Haresh Rochani, and Dr. Jingjing Yin worked collaboratively on this study.