Package: riskCommunicator
Title: G-Computation to Estimate Interpretable Epidemiological Effects
Version: 1.0.1
Authors@R: c(
    person(given = "Jessica",
           family = "Grembi",
           role = c("aut", "cre", "cph"),
           email = "jess.grembi@gmail.com",
           comment = c(ORCID = "0000-0001-6142-4913")),
           person("Elizabeth", "Rogawski McQuade", role = "ctb", comment = c(ORCID = "0000-0002-4942-3747")))
Depends: R (>= 3.5)
Imports: boot, dplyr, ggplot2, ggpubr, magrittr, MASS, methods, purrr,
        rlang, stats, tidyr, tidyselect
Description: Estimates flexible epidemiological effect measures including both differences and ratios using the parametric G-formula developed as an alternative to inverse probability weighting.  It is useful for estimating the impact of interventions in the presence of treatment-confounder-feedback. G-computation was originally described by Robbins (1986) <doi:10.1016/0270-0255(86)90088-6> and has been described in detail by Ahern, Hubbard, and Galea (2009) <doi:10.1093/aje/kwp015>; Snowden, Rose, and Mortimer (2011) <doi:10.1093/aje/kwq472>; and Westreich et al. (2012) <doi:10.1002/sim.5316>.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.2.0
Suggests: knitr, rmarkdown, testthat, tidyverse, printr, stringr,
        formatR, sandwich
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2022-05-31 21:06:05 UTC; JGrembi
Author: Jessica Grembi [aut, cre, cph]
    (<https://orcid.org/0000-0001-6142-4913>),
  Elizabeth Rogawski McQuade [ctb]
    (<https://orcid.org/0000-0002-4942-3747>)
Maintainer: Jessica Grembi <jess.grembi@gmail.com>
Repository: CRAN
Date/Publication: 2022-05-31 23:20:02 UTC
Built: R 4.1.3; ; 2023-04-17 20:52:02 UTC; windows
