Conducts sensitivity analyses for unmeasured confounding for either an observational study or a metaanalysis of observational studies. For a single observational study, the package reports Evalues, defined as the minimum strength of association on the risk ratio scale that an unmeasured confounder would need to have with both the treatment and the outcome to fully explain away a specific treatmentoutcome association, conditional on the measured covariates. One can use one of the evalues.XX() functions to compute Evalues for the relevant outcome types. Outcome types include risk ratios, odds ratio with common or rare outcomes, hazard ratios with common or rare outcomes, and standardized differences in outcomes. Optionally, one can use the bias_plot() function to plot the bias factor as a function of two sensitivity parameters. (See VanderWeele & Ding, 2017 [
Package details 


Author  Maya B. Mathur, Peng Ding, Tyler J. VanderWeele 
Date of publication  20171129 13:30:59 UTC 
Maintainer  Maya B. Mathur <[email protected]> 
License  GPL2 
Version  1.1.0 
Package repository  View on CRAN 
Installation 
Install the latest version of this package by entering the following in R:

Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.