propensity-package: propensity: A Toolkit for Calculating and Working with...

In propensity: A Toolkit for Calculating and Working with Propensity Scores

propensity: A Toolkit for Calculating and Working with Propensity Scores

Description

propensity provides tools for propensity score analysis in causal inference. Calculate propensity score weights for a variety of causal estimands, handle extreme propensity scores through trimming, truncation, and calibration, and estimate causal effects with inverse probability weighting. The package supports binary, categorical, and continuous exposures.

Weight functions

Calculate propensity score weights for different causal estimands:

• wt_ate(): Average treatment effect (ATE) weights

• wt_att(): Average treatment effect on the treated (ATT) weights

• wt_atu(): Average treatment effect on the untreated (ATU) weights (wt_atc() is an alias)

• wt_atm(): Average treatment effect for the evenly matchable (ATM) weights

• wt_ato(): Average treatment effect for the overlap population (ATO) weights

• wt_entropy(): Entropy balancing weights

• wt_cens(): Censoring weights

Propensity score modifications

Handle extreme propensity scores before calculating weights:

• ps_trim(): Trim observations with extreme propensity scores

• ps_trunc(): Truncate (winsorize) extreme propensity scores

• ps_calibrate(): Calibrate propensity scores to improve balance

• ps_refit(): Re-estimate the propensity score model after trimming

Estimation

• ipw(): Inverse probability weighted estimator with variance estimation that accounts for propensity score estimation uncertainty

PSW class

The psw() class represents propensity score weights with metadata about the estimand and modifications applied:

• psw(), as_psw(), is_psw(): Create and test propensity score weights

• estimand(): Query the causal estimand

• is_stabilized(): Check if weights are stabilized

Author(s)

Maintainer: Malcolm Barrett [e-mail] (ORCID) [copyright holder]

See Also

• vignette("propensity") for a getting started guide

• The package website for full documentation

propensity documentation built on March 3, 2026, 1:06 a.m.