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pstratreg

Regression-Based Principal Stratification

Ian updating as an example

WARNING. This website documents an R package that is in development. Expect changes. We encourage you to try the package and email us with suggestions. Project is joint work by Ian Lundberg (ilundberg@cornell.edu) and Soonhong Cho (soonhongcho@g.ucla.edu).

This website documents the pstratreg package for R. The package helps study causal effects when some treatment values cause outcomes to be non-existent for some units.

Possible applications include

• a labor market intervention where the outcome is hourly wage, but some people are unemployed
• a medical intervention where the outcome is a health metric, but some people die before it is measured
• a sociological study where the outcome involves one’s spouse, but some people divorce or never marry and thus have no spouse

This package provides regression-based methods for principal stratification that rely on parametric models and are useful in settings where one hopes to adjust for many confounders.

Getting started

To get started, first install R and RStudio. Then install the package.

{r, eval = F} devtools::install_github("ilundberg/pstratreg")

Now head on to the next page to see the types of questions this package can help answer.

This project is joint work between Ian Lundberg (Cornell, ilundberg@cornell.edu) and Soonhong Cho (UCLA, soonhongcho@g.ucla.edu).

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.