Package: tipr
Type: Package
Title: Tipping Point Analyses
Version: 0.3.0
Author: Lucy D'Agostino McGowan
Maintainer: Lucy D'Agostino McGowan <lucydagostino@gmail.com>
Description: 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.
License: MIT + file LICENSE
Encoding: UTF-8
RoxygenNote: 7.1.1
Suggests: testthat, broom, dplyr, MASS
Imports: glue, tibble, purrr
NeedsCompilation: no
Packaged: 2021-09-09 19:31:54 UTC; lucymcgowan
Repository: CRAN
Date/Publication: 2021-09-10 08:00:02 UTC
Built: R 4.0.2; ; 2021-09-11 10:37:46 UTC; unix
