Date(s) - 11/10/2017 - 11/11/2017
9:00 am - 5:00 pm
Like regression analysis, propensity score analysis allows you to adjust for many potentially confounding variables. What makes propensity score methods different is that the results are easier to communicate to lay audiences. And propensity score estimates are often more robust to differences in the distributions of the confounding variables. This seminar provides a comprehensive introduction to propensity score methodology. It will focus on three closely related methods: propensity score matching and related methods, including greedy matching, optimal matching, and propensity score weighting, matching estimators, and propensity score analysis with non-parametric regression.
Those who attend should be engaged in intervention research, program evaluation, or more generally causal inference. Attendees should have knowledge of multiple regression analysis.
The course will be taught by Dr. Shenyang Guo on
November 10 and 11, in Chicago, Illinois. The course is outlined on the website HERE, as well as additional course material and information.
Before registering note that there early and late registration fees. Early registration ends on October 11. To register for the seminar please click HERE.