R packages

AIPW

Augmented inverse probability weighting

https://doi.org/10.1093/aje/kwab207 GitHub

Augmented inverse probability weighting (AIPW) is a doubly robust estimator for causal inference. The AIPW package is designed for estimating the average treatment effect of a binary exposure on risk difference (RD), risk ratio (RR) and odds ratio (OR) scales with user-defined stacked machine learning algorithms (SuperLearner or sl3).

relate

REcursive muLtivariAte TEsting for cohort clustering

GitHub

The goal of relate is to identify cohort cluster with disparate covariate information. This package uses unsupervised random forests to obtain distances between observations within and across cohorts, hierarchical clustering to identify sub-groups of cohorts, and then test whether covariate distributions provide evidence differences in multivariate joint distributions.