LDECOMP: Stata module decomposing the total effects in a logistic regression into direct and indirect effects

ldecomp decomposes the total effects of a categorical variable in logistic regresion into direct and indirect effects using a method method by Erikson et al. (2005) and a generalization of this method by Buis (2008). Consider an example where social class has an indirect effect on attending college through academic performance in high school. The indirect effect is obtained by comparing the proportion of lower class students that attend college with the counterfactual proportion of lower class students if they had the distribution of performance of the higher class students. This captures the association between class and attending college due to differences in performance. The direct effect of class is obtained by comparing the proportion of higher class students with the counterfactual proportion of lower class students if they had the same distribution of performance as the higher class students. This way the variable performance is kept constant. If these comparisons are carried out in the form of log odds ratios than the total effect will equal the sum of the direct and indirect effects. In its original form this method assumes that the variable through which the indirect effect occurs is normally distributed. This is generalized by Buis (2008) by allowing this variable to have any distribution, which has the added advantage of simplifying the method.