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treatment

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This is a Python tool to employ stratified sampling or treatment randomization with uneven numbers in some strata using pandas. Mainly thought with RCTs in mind, it also works for any other scenario in where you would like to randomly allocate treatment within blocks or strata. The tool also supports having multiple treatments with different pro…

  • Updated May 6, 2024
  • Python

This repository contains the implementation of ITErpretability, a new framework to benchmark treatment effect deep neural network estimators with interpretability. For more details, please read our NeurIPS 2022 paper: 'Benchmarking Heterogeneous Treatment Effect Models through the Lens of Interpretability'.

  • Updated Mar 29, 2023
  • Jupyter Notebook

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