Basic Sensitivity Analysis of Epidemiological Results
Bootstrap resampling for selection and misclassification bias models.
Sensitivity analysis for unmeasured confounders based on confounding i...
Compute E-value to assess bias due to unmeasured confounder.
Sensitivity analysis for unmeasured confounders based on external adju...
Bounding the bias limits of unmeasured confounding.
Uncontrolled confounding
episensr : Basic Sensitivity Analysis for Epidemiological Results
Sensitivity analysis to correct for selection bias caused by M bias.
Covariate misclassification
Misclassification of exposure or outcome
Multidimensional sensitivity analysis for different sources of bias
Pipe bias functions
Plot of bootstrap simulation output for selection and misclassificatio...
Plot(s) of probabilistic bias analyses
Plot DAGs before and after conditioning on collider (M bias)
Print bootstrapped confidence intervals
Print associations for episensr class
Print association corrected for M bias
Legacy version of probsens().
Legacy version of probsens.conf().
Legacy version of probsens.irr().
Legacy version of probsens.irr.conf().
Probabilistic sensitivity analysis for unmeasured confounding of perso...
Probabilistic sensitivity analysis for exposure misclassification of p...
Selection bias.
Basic sensitivity analysis of the observed relative risks adjusting for unmeasured confounding and misclassification of the exposure/outcome, or both. It follows the bias analysis methods and examples from the book by Fox M.P., MacLehose R.F., and Lash T.L. "Applying Quantitative Bias Analysis to Epidemiologic Data, second ed.", ('Springer', 2021).
Useful links