dte_adj is a Python package for estimating distribution treatment effects. It provides APIs for conducting regression adjustment to estimate precise distribution functions as well as convenient utils.
A package of wrapper functions that are useful when analyzing data from randomized controlled trials (RCTs, especially with three or more treatment assignments)
Presentation on principal component analysis with an application.
An end-to-end R workflow for analyzing a real randomized email experiment using the Hillstrom MineThatData Email Analytics Challenge dataset.
Credit rate cards from a randomised interest-rate experiment (53,810 loan offers): exact replication, doubly robust off-policy evaluation on held-out branches, policy trees and a Monte Carlo campaign P&L.
Randomized survey experiment testing whether "Limited Edition" labeling changes what consumers buy — a full causal-inference workflow (randomization & balance checks, ATE, FDR correction, power/MDE) in Python.
Tutorial on average marginal effects over time in a randomized controlled trial using R.
Four ways to measure cause and effect in R: a field experiment, a randomized trial, CAPM regression and difference-in-differences, each on real data from a published study.
Reproducible reanalysis of ISTDP vs. waitlist data for treatment-resistant depression using papaja and R
Inferencia causal de un programa de mantenimiento de flota minera: uplift (S/T/X-learner, Causal Forest, DR-Learner) y DiD escalonado, validados contra la verdad conocida de datos simulados y contra datos reales (mpdta, Hillstrom). Pruebas y CI en verde.
Multi-agent causal simulation of 1,000 AI-agent couples in Rust (Bevy ECS) and Python. Randomized controlled trials on agent memory with bootstrap CIs, permutation tests, placebo and counterfactual twins, and SHA-256 replay. A React and PixiJS 2D world, plus a Claude LLM that turns plain-language shocks into validated, deterministic inputs.
Code for the knapsack difficulty project
PRISMA 2020 and CONSORT 2025 flow diagram examples as editable Mermaid text, with SVG/PNG exports and JSON count-closure checks. Made with diagramgen.app. Not affiliated with the PRISMA or CONSORT groups. CC BY 4.0.
Toll-road customer, pricing and transportation decision intelligence: causal targeting, a Gurobi-certified campaign MIP, a 10-arm randomised trial, HTML/CSS Power BI and a Databricks job. Synthetic data.
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