This talk overviews some recently developed SAS software tools for causal analysis, including causal effect estimation, causal mediation analysis, and causal graph theory for establishing valid estimation strategies. After basic principles of causal analysis are summarized, important features of the software tools are demonstrated through examples.

Clay Thompson is a principal research statistician developer in Advanced Analytics R&D at SAS Institute, Inc. In addition to developing and supporting tools for causal analysis, he has taught workshops and CE courses on causal analysis at multiple international conferences. His work also includes numerical methods for differential equation models, factor analysis, and the design and analysis of sequential trials. Prior to joining SAS, Clay worked as a quantitative systems pharmacologist at Pfizer Inc. He received his PhD in applied mathematics from NCSU.