average-treatment-effect

Simulation for "Method-of-Moments Inference for GLMs and Doubly Robust Functionals under Proportional Asymptotics"

End-to-end causal inference study estimating the effect of smoking cessation on substantial weight gain using propensity methods, DoWhy, and doubly robust EconML estimators.

Propensity score matching estimators for QTE, QTT, ATE, and ATT in R.

A comparative performance study of Propensity Score Matching, Doubly Robust Estimation, and Stratification algorithms. Evaluates Average Treatment Effect (ATE) accuracy and computational runtime across high-dimensional and low-dimensional datasets using L1-penalized propensity score estimation.

Couse project focused on determining the causal effect of being in a technical-vocational course in the Philippines to getting employment. In partial fulfillment of the requirements in Stat 197: Causal Inference in collaboration with Niña Martin & Jerwind Pineda.

Production-style A/B testing with binomial GLMs (logit/probit): covariate adjustment, marginal ATE/risks, cluster-robust SEs, and Brier-score calibration.