"No-one has ever called me a cool dude. I'm somewhere between geek and normal."
Linus Torvalds
Transforms NHANES survey data into clear, survey-style visual reports with built-in documentation
Interactive visualization of Medicaid expansion effects using causal inference
A code-first reference for causal inference and causal ML methods, with R and Python examples for each estimator.
An interactive browser-based tool for drawing and analyzing causal DAGs, with automatic identification of adjustment sets, backdoor paths, and variable roles.