PSA

Propensity Score Analysis (PSA) is a statistical approach for estimating causal effects from observational studies. This project includes materials from workshops taught, an Shiny application for conducting PSA, and an early draft of a PSA book.

R Package and Shiny Application for the Analysis of Qualitative Data.

An R Package to Support Propensity Score Analysis.

Propensity score matching for non-binary treatments.

An R package for estimating and visualizing multilevel propensity score models.

I am happy to announce that version 1.0 of the PSAboot package has been released to CRAN. This package implements bootstrapping for propensity score analysis. This deviates from typical implementations such as boot in that it allows for separate sampling specifications for treatment and control units. For example, in the case where the ratio of treatment-to-control units is large, one can bootstrap only the control units while always using all available treatment units.