CausalLift: Python package for causality-based Uplift Modeling in real-world business

📦 R/haldensify: Highly Adaptive Lasso Conditional Density Estimation

Bootstrapping for Propensity Score Analysis

Targeted maximum likelihood estimation (TMLE) enables the integration of machine learning approaches in comparative effectiveness studies. It is a doubly robust method, making use of both the outcome model and propensity score model to generate an unbiased estimate as long as at least one of the models is correctly specified.

Lecture slides, video recordings, and coding exercises from the 2024 Northwestern University Causal Inference Workshop. This repository is not affiliated with Northwestern University or the workshop.

do the green drivers also drive longer? --- causal identification using the propensity score approach

counterfactual matching

Multinomial Propensity Score Trimming (Am J Epidemiol 2018)

TI Methods Speaker Series in collaboration with the Student and Recent Graduate Committee (SARGC) of the Statistical Society of Canada.

Propensity Score Analysis Graphics

How to use the Machine Learning Runtime and MLflow on top of a health Delta Lake to predict patient disease

R package for propensity score weighting using machine learning methods

implement machine learning models from scratch

Comparison of treatment effect in Randomized Control Trial (RCT) and Propensity Score Matching methods, conducted on Large-Scale Dataset by 'Criteo'.

Propensity scores in complex surveys

Measuring the effect of diagnostic delays of fungal pathogens on healthcare costs in a commercially insured population. Linked Marketscan ICD-10 data on symptom and diagnosis dates. Quantile binning probability weighting was used to account for the causal relationship of time. Categorical regressions were conducted for a zero-inflated exposure.

R code for the analyses conducted in Friedrich, S & Friede, T (2020). Causal inference methods for small non-randomized studies: Methods and an application in COVID-19. Submitted to Contemporary Clinical Trials.

Propensity score assignment

Code and presentation for project utilizing causal inference to determine the impacts of high physical activity on mortality using data from the National Health and Nutrition Examination Survey (NHANES). Results of hackathon at University of Minnesota Equitable Data Science in Adolescent Development REU.

Conducted an inverse probability weighted survival analysis in State Veteran Home facilities which investigated the hazard of being infected by COVID among varying vaccination doses and types. Involved complex data linkages to person-level and facility-level data and creating a nested control group of those who didn’t receive bivalent booster