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    • Code for paper: "The parametric G-formula for time-to-event data: towards intuition with a worked example"
      SAS
      0300Updated Nov 1, 2024Nov 1, 2024
    • R
      GNU General Public License v3.0
      0000Updated Oct 14, 2023Oct 14, 2023
    • SAS
      GNU General Public License v3.0
      1100Updated May 9, 2023May 9, 2023
    • For the "GitHub for Epidemiologists" workshop on 2023-03-31.
      Rebol
      MIT License
      3000Updated Mar 31, 2023Mar 31, 2023
    • CausalBot

      Public
      I retweet #CausalTwitter
      Julia
      GNU General Public License v3.0
      1100Updated Apr 21, 2022Apr 21, 2022
    • Code to accompany the paper "Bayesian G-Computation to Estimate Impacts of Interventions on Exposure Mixtures: Demonstration with Metals from Coal-fired Power Plants and Birthweight"
      Julia
      GNU General Public License v3.0
      0100Updated Apr 19, 2021Apr 19, 2021
    • Code to accompany the manuscript "13 Questions About Using Machine Learning in Causal Research (You Won’t Believe the Answer to Number 10!)"
      SAS
      GNU General Public License v3.0
      0200Updated Mar 17, 2021Mar 17, 2021
    • Materials for: An introduction to transporting treatment effects from randomized clinical trials to clinical practice (SER 2020 pre-conference workshop)
      R
      0000Updated Jan 8, 2021Jan 8, 2021
    • Super learner: super learning (stacking) in the SAS system
      SAS
      GNU General Public License v3.0
      2100Updated Jul 20, 2020Jul 20, 2020
    • Code from paper "A Bayesian approach to the g-formula"
      Stan
      0800Updated May 15, 2020May 15, 2020
    • An implementation of the SuperLearner algorithm in Python based on scikit-learn. (py3 compatible)
      Python
      MIT License
      11100Updated May 23, 2017May 23, 2017