EDUC 3418 - CAUSAL MODERATION AND MEDIATION ANALYSIS
This course is designed for graduate students who are interested in applying advanced quantitative methods to their research. Research questions regarding how, for whom, and where a treatment achieves its effect on an outcome are often key to the advancement of scientific knowledge and have become increasingly valued in various fields. Such questions can be answered by causal moderation and mediation analysis, which assesses the heterogeneity of the treatment effect across individual and contextual characteristics and uncovers the mediation mechanism underlying the treatment effect. This course introduces the theoretical concepts of moderated effects and mediated effects under the potential outcomes framework, cutting-edge methodological approaches, and how to implement the methods with user-friendly R packages. The course blends theory and applications -- avoiding the extremes of presenting unneeded theory in isolation, or of giving application tools without the foundation needed for practical understanding. Prerequisites of the course are Introduction to Statistics and Introduction to Causal Inference or their equivalents.