tag:joss.theoj.org,2005:/papers/tagged/confoundingJournal of Open Source Software2024-03-09T11:15:15ZJournal of Open Source Softwarehttps://joss.theoj.orgtag:joss.theoj.org,2005:Paper/46362024-03-09T11:15:15Z2024-03-10T00:01:20Zkonfound: An R Sensitivity Analysis Package to Quantify the Robustness of Causal Inferencesaccepted0.4.02023-07-31 19:56:25 UTC952024-03-09 11:15:15 UTC920245779SarahNarvaizUniversity of Tennessee, Knoxville, Knoxville, TN, USAQinyunLinUniversity of Gothenburg, Gothenburg, SEJoshuaM.RosenbergUniversity of Tennessee, Knoxville, Knoxville, TN, USAKennethA.FrankMichigan State University, East Lansing, MI, USASpiroJ.MaroulisArizona State University, Tempe, AZ, USAWeiWangUniversity of Tennessee, Knoxville, Knoxville, TN, USARanXuUniversity of Connecticut, Hartford, CT, USA10.21105/joss.05779https://doi.org/10.5281/zenodo.10708094Rhttps://joss.theoj.org/papers/10.21105/joss.05779.pdfSensitivity analysis, Causal inferencetag:joss.theoj.org,2005:Paper/35922022-09-05T11:14:39Z2023-10-08T07:24:41Ztipr: An R package for sensitivity analyses for unmeasured confoundersacceptedv0.4.12022-05-06 16:58:03 UTC772022-09-05 11:14:39 UTC720224495LucyD\'AgostinoMcGowanWake Forest University, USA0000-0001-7297-935910.21105/joss.04495https://doi.org/10.5281/zenodo.6958926Rhttps://joss.theoj.org/papers/10.21105/joss.04495.pdfstatistics, epidemiology, sensitivity analyses, causal inference, confounding