DESCRIPTION

Type: Package
Package: tipr
Title: Tipping Point Analyses
Version: 1.0.2.9000
Authors@R: c(
    person("Lucy", "D'Agostino McGowan", , "lucydagostino@gmail.com", role = c("aut", "cre"),
           comment = c(ORCID = "0000-0002-6983-2759")),
    person("Malcolm", "Barrett", , "malcolmbarrett@gmail.com", role = "aut",
           comment = c(ORCID = "0000-0003-0299-5825"))
  )
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, the
    relationship between an unmeasured confounder and the outcome, for
    example a plausible residual effect size for an unmeasured continuous
    or binary confounder, and the relationship between an unmeasured
    confounder and the exposure, for example a realistic mean difference
    or prevalence difference for this hypothetical confounder between
    exposure groups. Building on the methods put forth by Cornfield et al.
    (1959), Bross (1966), Schlesselman (1978), Rosenbaum & Rubin (1983),
    Lin et al. (1998), Lash et al. (2009), Rosenbaum (1986), Cinelli &
    Hazlett (2020), VanderWeele & Ding (2017), and Ding & VanderWeele
    (2016), we can use these quantities to assess how an unmeasured
    confounder may tip our result to insignificance.
License: MIT + file LICENSE
URL: https://r-causal.github.io/tipr/, https://github.com/r-causal/tipr
BugReports: https://github.com/r-causal/tipr/issues
Depends: 
    R (>= 2.10)
Imports:
    cli (>= 3.4.1),
    glue,
    purrr,
    rlang (>= 1.0.6),
    sensemakr,
    tibble
Suggests:
    broom,
    dplyr,
    MASS,
    testthat
Encoding: UTF-8
LazyData: true
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.1