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  "Version": "0.0.3",
  "Date": "2024-03-05",
  "Title": "Simulation-Based Sensitivity Analysis for Causal Mediation\nStudies",
  "Author": "Xu Qin and Fan Yang",
  "Maintainer": "Xu Qin <xuqin@pitt.edu>",
  "Description": "Simulation-based sensitivity analysis for causal mediation\nstudies. It numerically and graphically evaluates the\nsensitivity of causal mediation analysis results to the\npresence of unmeasured pretreatment confounding. The proposed\nmethod has primary advantages over existing methods. First,\nusing an unmeasured pretreatment confounder conditional\nassociations with the treatment, mediator, and outcome as\nsensitivity parameters, the method enables users to intuitively\nassess sensitivity in reference to prior knowledge about the\nstrength of a potential unmeasured pretreatment confounder.\nSecond, the method accurately reflects the influence of\nunmeasured pretreatment confounding on the efficiency of\nestimation of the causal effects. Third, the method can be\nimplemented in different causal mediation analysis approaches,\nincluding regression-based, simulation-based, and propensity\nscore-based methods. It is applicable to both randomized\nexperiments and observational studies.",
  "License": "GPL-2",
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  "Date/Publication": "2024-03-07 02:29:00 UTC",
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      "role": "Depends"
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    "extra/citation.html",
    "extra/citation.json",
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      "title": "Simulation-Based Sensitivity Analysis Table for Causal Mediation Analysis",
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