Basic Sensitivity Analysis of Epidemiological Results

boot.bias | Bootstrap resampling for selection and misclassification bias... |

confounders | Sensitivity analysis to correct for unknown or unmeasured... |

confounders.array | Sensitivity analysis for unmeasured confounders based on... |

confounders.emm | Sensitivity analysis to correct for unknown or unmeasured... |

confounders.evalue | Compute E-value to assess bias due to unmeasured confounder. |

confounders.ext | Sensitivity analysis for unmeasured confounders based on... |

confounders.limit | Bounding the bias limits of unmeasured confounding. |

confounders.poly | Sensitivity analysis to correct for unknown or unmeasured... |

episensr-package | episensr: Basic sensitivity analysis of epidemiological... |

mbias | Sensitivity analysis to correct for selection bias caused by... |

misclassification | Sensitivity analysis for disease or exposure... |

misclassification_cov | Sensitivity analysis for covariate misclassification. |

multidimBias | Multidimensional sensitivity analysis for different sources... |

multiple.bias | Extract adjusted 2-by-2 table from episensr object |

pipe | Pipe bias functions |

plot.episensr.booted | Plot of bootstrap simulation output for selection and... |

plot.mbias | Plot DAGs before and after conditioning on collider (M bias) |

print.episensr | Print associations for episensr class |

print.episensr.booted | Print bootstrapped confidence intervals |

print.mbias | Print association corrected for M bias |

probsens | Probabilistic sensitivity analysis. |

probsens.conf | Probabilistic sensitivity analysis for unmeasured... |

probsens.irr | Probabilistic sensitivity analysis for exposure... |

probsens.irr.conf | Probabilistic sensitivity analysis for unmeasured confounding... |

probsens.sel | Probabilistic sensitivity analysis for selection bias. |

selection | Sensitivity analysis to correct for selection bias. |

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