konfound: An R Sensitivity Analysis Package to Quantify the Robustness of Causal Inferences

R Submitted 31 July 2023Published 09 March 2024
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Editor: @fabian-s (all papers)
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Authors

Sarah Narvaiz, Qinyun Lin, Joshua M. Rosenberg, Kenneth A. Frank, Spiro J. Maroulis, Wei Wang, Ran Xu

Citation

Narvaiz et al., (2024). konfound: An R Sensitivity Analysis Package to Quantify the Robustness of Causal Inferences. Journal of Open Source Software, 9(95), 5779, https://doi.org/10.21105/joss.05779

@article{Narvaiz2024, doi = {10.21105/joss.05779}, url = {https://doi.org/10.21105/joss.05779}, year = {2024}, publisher = {The Open Journal}, volume = {9}, number = {95}, pages = {5779}, author = {Sarah Narvaiz and Qinyun Lin and Joshua M. Rosenberg and Kenneth A. Frank and Spiro J. Maroulis and Wei Wang and Ran Xu}, title = {konfound: An R Sensitivity Analysis Package to Quantify the Robustness of Causal Inferences}, journal = {Journal of Open Source Software} }
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Sensitivity analysis Causal inference

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ISSN 2475-9066