Software
R packages
causalQual
Causal inference for qualitative outcomes
Your treatment reshaped how people rank their health, satisfaction, or job quality—but standard methods pretend the outcome is a number. causalQual gives you sharp, interpretable causal effects on every category of a qualitative outcome, plugging straight into IV, RDD, and DiD designs you already know.
valiCATE
Validation of CATE models
You estimated heterogeneous treatment effects—but can you trust them? valiCATE stress-tests any CATE model with best linear prediction, sorted group ATEs, and rank-weighted ATEs, so you know whether your personalized effects are signal or noise.
ocf
Ordered correlation forest
Stop forcing ordered outcomes into logit or probit boxes. ocf is a random forest tailor-made for ordered categories—delivering predictions and marginal effects with valid confidence intervals out of the box.
aggTrees
Aggregation trees
Who benefits most from a policy—and can you prove it? aggTrees automatically discovers the subgroups that matter, uses double machine learning for rigorous inference on each group's treatment effect, and lets you zoom from broad patterns to fine-grained heterogeneity without p-hacking.