riskCommunicator: G-Computation to Estimate Interpretable Epidemiological Effects
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>.
Version: |
1.0.1 |
Depends: |
R (≥ 3.5) |
Imports: |
boot, dplyr, ggplot2, ggpubr, magrittr, MASS, methods, purrr, rlang, stats, tidyr, tidyselect |
Suggests: |
knitr, rmarkdown, testthat, tidyverse, printr, stringr, formatR, sandwich |
Published: |
2022-05-31 |
DOI: |
10.32614/CRAN.package.riskCommunicator |
Author: |
Jessica Grembi
[aut, cre, cph],
Elizabeth Rogawski McQuade
[ctb] |
Maintainer: |
Jessica Grembi <jess.grembi at gmail.com> |
License: |
GPL-3 |
NeedsCompilation: |
no |
Materials: |
README NEWS |
In views: |
Epidemiology |
CRAN checks: |
riskCommunicator results |
Documentation:
Downloads:
Reverse dependencies:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=riskCommunicator
to link to this page.