| episensr-package | Basic sensitivity analysis of epidemiological results |
| confounders | Simple sensitivity analysis to correct for unknown or unmeasured confounding without effect modification |
| confounders, confounders.emm, confounders.limit | Simple sensitivity analysis to correct for unknown or unmeasured polychotomous confounding without effect modification |
| confounders, confounders.emm, confounders.poly | Bounding the bias limits of unmeasured confounding. |
| confounders, confounders.poly, confounders.limit | Simple sensitivity analysis to correct for unknown or unmeasured confounding with effect measure modification |
| confounders.emm | Simple sensitivity analysis to correct for unknown or unmeasured confounding with effect measure modification |
| confounders.emm, confounders.poly | Simple sensitivity analysis to correct for unknown or unmeasured confounding without effect modification |
| confounders.limit | Bounding the bias limits of unmeasured confounding. |
| confounders.poly | Simple sensitivity analysis to correct for unknown or unmeasured polychotomous confounding without effect modification |
| episensr | Basic sensitivity analysis of epidemiological results |
| misclassification | Simple sensitivity analysis for misclassification |
| multidimBias | Multidimensional sensitivity analysis for different sources of bias |
| probsens | Probabilistic sensitivity analysis. |
| probsens, probsens.conf | Probabilistic sensitivity analysis for selection bias. |
| probsens, probsens.sel | Probabilistic sensitivity analysis for unmeasured confounding. |
| probsens.conf | Probabilistic sensitivity analysis for unmeasured confounding. |
| probsens.conf, probsens.sel | Probabilistic sensitivity analysis. |
| probsens.sel | Probabilistic sensitivity analysis for selection bias. |
| selection | Simple sensitivity analysis to correct for selection bias using estimates of the selection proportions |