SuperNOVA: Semi-Parametric Identification and Estimation of Interaction and Effect Modification in Mixed Exposures using Stochastic Interventions in R

R Submitted 15 February 2023 • Published 05 November 2023
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Editor: @csoneson (all papers)
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Authors

David McCoy (0000-0002-5515-6307), Alejandro Schuler (0000-0003-4853-6130), Alan Hubbard (0000-0002-3769-0127), Mark van der Laan (0000-0003-1432-5511)

Citation

McCoy et al., (2023). SuperNOVA: Semi-Parametric Identification and Estimation of Interaction and Effect Modification in Mixed Exposures using Stochastic Interventions in R. Journal of Open Source Software, 8(91), 5422, https://doi.org/10.21105/joss.05422

@article{McCoy2023, doi = {10.21105/joss.05422}, url = {https://doi.org/10.21105/joss.05422}, year = {2023}, publisher = {The Open Journal}, volume = {8}, number = {91}, pages = {5422}, author = {David McCoy and Alejandro Schuler and Alan Hubbard and Mark van der Laan}, title = {SuperNOVA: Semi-Parametric Identification and Estimation of Interaction and Effect Modification in Mixed Exposures using Stochastic Interventions in R}, journal = {Journal of Open Source Software} }
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causal inference machine learning stochastic interventions efficient estimation targeted learning mixed exposures

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