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1. DNNcausal DNNcausal Public

   An R-package to estimate average causal effects with AIPW using Deep Neural Networks, in particular Convolutional NN.

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2. Causal_CNN Causal_CNN Public

   This repository includes supplementary material to the manuscript Ghasempour, Moosavi and de Luna (2023, Convolutional neural networks for valid and efficient causal inference).

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3. SDRcausal SDRcausal Public

   SDRcausal is a R Package that provides semiparametric estimators of Average Causal Effects, using sufficient dimension reduction for nuisance model estimation.

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4. COVID-19 COVID-19 Public

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   Novel Coronavirus (COVID-19) Cases, provided by JHU CSSE

5. hdim.ui hdim.ui Public

   hdim.ui - R package for sensitivity analysis in high-dimensional causal inference and missing outcome data contexts

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6. ate-1-step-estimator ate-1-step-estimator Public

   Forked from fileds/ate-1-step-estimator

   R Shiny app for visualisation of the 1-step estimator for the Average Treatment Effect (ATE).

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