There are 1 repository under propensity-score topic.
CausalLift: Python package for causality-based Uplift Modeling in real-world business
:package: R/haldensify: Highly Adaptive Lasso Conditional Density Estimation
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.
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.
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.
How to use the Machine Learning Runtime and MLflow on top of a health Delta Lake to predict patient disease
Comparison of treatment effect in Randomized Control Trial (RCT) and Propensity Score Matching methods, conducted on Large-Scale Dataset by 'Criteo'.
implement machine learning models from scratch
R package for propensity score weighting using machine learning methods
This R package contains a function to apply MARMoT balancing technique, a function for computing the Deloof's approximation of the average rank (and also a parallelized version) and a function to compute the Absolute Standardized Bias.
Replication of the paper "Voting Made Safe and Easy: The impact of e-voting on Citizen Perceptions," by Alvarez et. al and its extension using genetic matching.
These are R implementations under lasso related priors for clustering structure with propensity score, principal stratification and outcomes in Bayesian inference
A thesis project exploring the causal impact of urban parks on children's happiness, with data, results, and code.
Causal Inference - Does Critic Ratings affect Movie's Revenue
POM-PS tests for genetic associations of secondary traits from case-control GWAS.
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.
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.
Comparing effectiveness of the most common causal machine learning methods across various treatment effect, model complexities, data dimensions and sample sizes.
Propensity score assignment
Quantitative Methods for Studying Elites: Demonstration for R
my master's thesis project that studies the impact of UN MDG on US nonprofit industry spending