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average-treatment-effect

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DiogoRibeiro7 / ab-glm-abtest

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

python statistics reproducible-research calibration logistic-regression ab-testing causal-inference probit risk-ratio risk-difference covariate-adjustment randomized-experiments average-treatment-effect brier-score binomial-glm marginal-predictions cluster-robust-standard-errors user-level-clustering sandwich-se
  • Updated Nov 10, 2025
  • Python

zfang43 / Causal-Inference-ATE-Algorithms

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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.

python benchmarking data-science machine-learning high-dimensional-data statistical-analysis logistic-regression causal-inference stratification l1-regularization propensity-score-matching average-treatment-effect doubly-robust-inference
  • Updated Dec 28, 2025
  • Jupyter Notebook

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