Basic Sensitivity Analysis of Epidemiological Results

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Documentation for package ‘episensr’ version 1.3.0

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

episensr-package	episensr: Basic sensitivity analysis of epidemiological results
%>%	Pipe bias functions
boot.bias	Bootstrap resampling for selection and misclassification bias models.
confounders	Sensitivity analysis to correct for unknown or unmeasured confounding without effect modification
confounders.array	Sensitivity analysis for unmeasured confounders based on confounding imbalance among exposed and unexposed
confounders.emm	Sensitivity analysis to correct for unknown or unmeasured confounding in the presence of effect modification
confounders.evalue	Compute E-value to assess bias due to unmeasured confounder.
confounders.ext	Sensitivity analysis for unmeasured confounders based on external adjustment
confounders.limit	Bounding the bias limits of unmeasured confounding.
confounders.poly	Sensitivity analysis to correct for unknown or unmeasured polychotomous confounding without effect modification
episensr	episensr: Basic sensitivity analysis of epidemiological results
mbias	Sensitivity analysis to correct for selection bias caused by M bias.
misclassification	Sensitivity analysis for disease or exposure misclassification.
misclassification.cov	Sensitivity analysis for covariate misclassification.
multidimBias	Multidimensional sensitivity analysis for different sources of bias
multiple.bias	Extract adjusted 2-by-2 table from episensr object
plot.episensr.booted	Plot of bootstrap simulation output for selection and misclassification bias
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 confounding.
probsens.irr	Probabilistic sensitivity analysis for exposure misclassification of person-time data and random error.
probsens.irr.conf	Probabilistic sensitivity analysis for unmeasured confounding of person-time data and random error.
probsens.sel	Probabilistic sensitivity analysis for selection bias.
selection	Sensitivity analysis to correct for selection bias.