Date: March 26-April 4, 2018
Location: Goldfarb Hall, Room 132, Washington University in St. Louis
CSD Sponsored Workshop on “Propensity Score Analysis”, led by Shenyang Guo
Propensity score analysis is a relatively new and innovative class of statistical methods that has proven useful for evaluating the effects of treatments or interventions when using nonexperimental or observational data.
This seminar will focus on three closely related but technically distinct propensity score methods:
- Propensity score matching and related methods, including greedy matching, optimal matching, and propensity score weighting using Stata psmatch2, pweights and R optmatch
- Matching estimators using Stata nnmatch
- Propensity score analysis with nonparametric regression using Stata psmatch2 and lowess.
Workshop Outline
Monday, March 26, 2018
1. Overview
2. Conceptual Frameworks and Assumptions
Wednesday, March 28, 2018
3. Propensity Score Matching and Related Models (Part I)
Thursday, March 29, 2018
4. Propensity Score Matching and Related Models (Part II)
Monday, April 2, 2018
5. Matching Estimators
6. Kernel-based Matching Estimator
Wednesday, April 4, 2018
7. Rosenbaum’s Sensitivity Analysis
8. Debates and Directions of Future Development