txshift: Efficient estimation of the causal effects of stochastic interventions in R

R Submitted 20 May 2020Published 07 October 2020
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Editor: @marcosvital (all papers)
Reviewers: @klmedeiros (all reviews), @joethorley (all reviews)

Authors

Nima S. Hejazi (0000-0002-7127-2789), David Benkeser (0000-0002-1019-8343)

Citation

Hejazi et al., (2020). txshift: Efficient estimation of the causal effects of stochastic interventions in R. Journal of Open Source Software, 5(54), 2447, https://doi.org/10.21105/joss.02447

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causal inference machine learning two-phase sampling efficient estimation targeted learning stochastic intervention modified treatment policy

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