tipr: Tipping Point Analyses

The strength of evidence provided by epidemiological and observational studies is inherently limited by the potential for unmeasured confounding. We focus on three key quantities: the observed bound of the confidence interval closest to the null, a plausible residual effect size for an unmeasured continuous or binary confounder, and a realistic mean difference or prevalence difference for this hypothetical confounder. Building on the methods put forth by Lin, Psaty, & Kronmal (1998) <doi:10.2307/2533848>, we can use these quantities to assess how an unmeasured confounder may tip our result to insignificance, rendering the study inconclusive.

Version: 0.1.1
Imports: broom, tibble, purrr
Suggests: testthat
Published: 2017-11-28
Author: Lucy D'Agostino McGowan
Maintainer: Lucy D'Agostino McGowan <ld.mcgowan at vanderbilt.edu>
License: MIT + file LICENSE
NeedsCompilation: no
Materials: README NEWS
CRAN checks: tipr results


Reference manual: tipr.pdf
Package source: tipr_0.1.1.tar.gz
Windows binaries: r-devel: tipr_0.1.1.zip, r-release: tipr_0.1.1.zip, r-oldrel: tipr_0.1.1.zip
OS X El Capitan binaries: r-release: tipr_0.1.1.tgz
OS X Mavericks binaries: r-oldrel: tipr_0.1.1.tgz


Please use the canonical form https://CRAN.R-project.org/package=tipr to link to this page.