EPSY 6655, a PhD-level seminar class in Causal Inference, is being offered in Spring 2016 through the Educational Psychology Department. The course is both theoretical and applied. It takes a deep look at Rubin’s Causal Model as a framework which clarifies what can and cannot be learned about causal relationships from data. Rubin’s Causal model has proved useful as a starting point for understanding famous paradoxes such as Lord’s paradox and Simpson’s paradox and as a tool for clarifying the assumptions underlying common techniques for exploring causality using data. It also provides the foundation for methods of causal inference based on propensity scores. All of these themes will be explored in this discussion based class.
In addition, students will learn how to estimate and use propensity scores for causal inference using the R software. They will also learn how to use new techniques for exploring mediation and moderation, such as ratio of mediator probability weighting and marginal mean weighting. Grading is based on completion of assigned readings, brief data analysis assignments and a final term paper. For more information about the class, contact the instructor, Dr. Christopher Rhoads at christopher.rhoads@uconn.edu
For more information, contact: Christopher Rhoads at christopher.rhoads@uconn.edu