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episensr (version 0.7.1)

Basic Sensitivity Analysis of Epidemiological Results

Description

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 Lash T.L, Fox M.P, and Fink A.K. "Applying Quantitative Bias Analysis to Epidemiologic Data", 'Springer', 2009.

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Install

install.packages('episensr')

Monthly Downloads

674

Version

0.7.1

License

GPL-2

Maintainer

Denis Haine

Last Published

October 5th, 2015

Functions in episensr (0.7.1)

print.mbias

Print association corrected for M bias
confounders.emm

Sensitivity analysis to correct for unknown or unmeasured confounding with effect modification
episensr

Basic sensitivity analysis of epidemiological results
probsens.irr.conf

Probabilistic sensitivity analysis for unmeasured confounding of person-time data and random error.
multidimBias

Multidimensional sensitivity analysis for different sources of bias
probsens.conf

Probabilistic sensitivity analysis for unmeasured confounding.
plot.mbias

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

Sensitivity analysis to correct for selection bias caused by M bias.
probsens.irr

Probabilistic sensitivity analysis for exposure misclassification of person-time data and random error.
confounders.poly

Sensitivity analysis to correct for unknown or unmeasured polychotomous confounding without effect modification
confounders

Sensitivity analysis to correct for unknown or unmeasured confounding without effect modification
misclassification

Sensitivity analysis for misclassification.
probsens

Probabilistic sensitivity analysis.
selection

Sensitivity analysis to correct for selection bias.
confounders.limit

Bounding the bias limits of unmeasured confounding.
probsens.sel

Probabilistic sensitivity analysis for selection bias.