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.