Conducts sensitivity analyses for unmeasured confounding in randomeffects metaanalysis per Mathur & VanderWeele (in preparation). Given output from a randomeffects metaanalysis with a relative risk outcome, computes point estimates and inference for: (1) the proportion of studies with true causal effect sizes more extreme than a specified threshold of scientific significance; and (2) the minimum bias factor and confounding strength required to reduce to less than a specified threshold the proportion of studies with true effect sizes of scientifically significant size. Creates plots and tables for visualizing these metrics across a range of bias values. Provides tools to easily scrape studylevel data from a published forest plot or summary table to obtain the needed estimates when these are not reported.
Package details 


Author  Maya B. Mathur, Tyler J. VanderWeele 
Date of publication  20170814 13:17:55 UTC 
Maintainer  Maya B. Mathur <[email protected]> 
License  GPL2 
Version  1.3.0 
Package repository  View on CRAN 
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