R packages
AIPW
Augmented inverse probability weighting
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
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.