New Weighting Methods for Causal Mediation Analysis
This course teaches the Ratio-of-Mediator-Probability Weighting (RMPW) method for decomposing total effects into direct and indirect effects in the presence of treatment-by-mediator interactions. RMPW is easy to implement and requires relatively few assumptions about the distribution of the outcome, the distribution of the mediator, and the functional form of the outcome model. Instructors will introduce the concepts of causal mediation, explain the intuitive rationale of the RMPW strategy, and delineate the parametric and nonparametric analytic procedures. Participants will gain hands-on experiences with a stand-alone RMPW software program that eases computation and facilitates users’ analytic decision-making. The instructors will also provide SPSS, SAS, Stata, and R code for interested users. The target audience includes graduate students, early career scholars, and advanced researchers who are familiar with multiple regression and have had prior exposure to binary and multinomial logistic regression. Prior knowledge of causal inference is not required but will be a major plus. Each participant will need to bring a laptop for hands-on exercises.
- Guanglei Hong, University of Chicago
- Jonah Deutsch, University of Chicago