Tooluniverse Statistical Modeling

This is a stats workhorse built for biomedical and clinical trial data, wrapping R and Python libraries into scripts that know the domain-specific gotchas. It handles natural spline regression (via R's `ns()`, not patsy approximations), ordinal logistic models for AE severity with proper SDTM encoding handling, per-gene ANOVA workflows that avoid naive pooling, and power analyses. The scripts enforce workspace isolation so your input data stays clean, and the rule-zero philosophy is smart: check for pre-computed results before re-running anything. If you're doing clinical trial stats or gene expression modeling and tired of debugging why your spline fit doesn't match the paper's R output, this saves the round trips.

Install to Claude Code

npx -y skills add mims-harvard/tooluniverse --skill tooluniverse-statistical-modeling --agent claude-code