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 formhttps://CRAN.R-project.org/package=riskCommunicatorto link to this page.