Confound-isolating cross-validation approach to control for a confounding effect in a predictive model.

Conquering confounds and covariates: methods, library and guidance

NeurIPS 2024 (spotlight): A Textbook Remedy for Domain Shifts Knowledge Priors for Medical Image Analysis

☯︎[ACMMM'22] Official PyTorch Implementation of Towards Unbiased Visual Emotion Recognition via Causal Intervention

A library for minimizing the effects of confounding covariates

Shiny-Tool for investigation of metabolite-covariate relationships

SNP abundance correlates with network degree

Source code for off-policy evaluation and optimization in the presence of unobserved confounding, accepted to AISTATS 2024.

Accounting for hidden confounders in estimates of dose-response curves from observational data.

Code for a probabilistic sensitivity analysis of an unmeasured confounder

An R-Package to perform Time-Dependent Matching for Observational Data in Discrete and Continuous Time

Coursework, Stata code, and notes for PBHS 31001: Epidemiologic Methods (Winter 2024, University of Chicago). Topics include bias, confounding, effect modification, cohort and case-control study design, and logistic/Poisson regression. The course emphasizes observational study design and practical applications using Stata.

Stratified Analysis using R - Beginner Level

Explore PBHS 31001: Epidemiologic Methods at UChicago. Access coursework, notes, and Stata code for mastering observational study designs. 📊📈

blopmatch: Matching Estimator based on a Bilevel Optimization Problem

Comparison of different methods for adjusting for confounding in a Cox regression using simulated data in stata

Semiparametric inference for relative heterogeneous vaccine efficacy between strains in observational case-only studies

code for paper on automating confounder control methods

R code for the Shiny app that accompanies Westfall & Yarkoni (2016)