Abstract
The propensity score, which was originally introduced in Rosenbaum and Rubin (1983), has been widely considered one of the most important concepts in the causal inference literature. This article briefly reviews some propensity score models involving both observed and unobserved covariates and discusses their applications in sensitivity analysis for matched observational studies.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 35-41 |
| Number of pages | 7 |
| Journal | Observational Studies |
| Volume | 9 |
| Issue number | 1 |
| DOIs | |
| State | Published - 2023 |
Keywords
- Fisher’s sharp null
- Generalized propensity score
- Matching
- Neyman’s weak null
- Randomization inference
- Unmeasured confounding
ASJC Scopus subject areas
- Applied Mathematics
- Numerical Analysis
- Statistics and Probability
- Computer Science Applications
- Modeling and Simulation