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.episensr.probsens | Plot(s) of probabilistic bias analyses |
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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