Causal Inference with Observational Data
Half Day Short Course | Register here
2026 APSA Annual Meeting & Exhibition — Boston, MA
9:00 am – 1:00 pm
Estimating treatment effects when the data are observational rather than experimental presents a challenge in many research areas. This course provides an introduction into the problems of causal inference that arise in the context of observational data, and presents an overview of statistical methods and techniques to overcome these challenges. Commonly used techniques for estimating treatment effects such as regression adjustment, inverse-probability weighting, and propensity-score matching will be discussed. In addition, we will also present techniques for performing model checking and model selection, and we will introduce methods for dealing with more complex causal models such as causal mediation models. Finally, we will present a number of hands-on examples that demonstrate how to perform causal inference and treatment effect estimation. The examples are shown using the statistical software package Stata, but no prior knowledge of Stata is required. Attendees should be familiar with basic statistical methods and techniques such as regression modeling.
- APSA Annual Meeting Pre-conference Short Courses are half- or full-day events that offer diverse professional development opportunities and allow attendees to connect with scholars from various backgrounds. This year’s pre-conference short courses will be held on Wednesday, September 2, 2026, in Boston, Massachusetts. Sponsored by APSA Organized Sections, Related Groups, and other affiliated organizations. All short courses require pre-registration to attend.
- Register here for the APSA Annual Meeting & Exhibition »
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