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riskCommunicator

G-Computation to Estimate Interpretable Epidemiological Effects

v1.0.1 · May 31, 2022 · GPL-3

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>.

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OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 9, 2026

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Dependency Network

Dependencies Reverse dependencies boot dplyr ggplot2 ggpubr magrittr MASS purrr rlang tidyr tidyselect BiVariAn riskCommunicator

Version History

new 1.0.1 Mar 10, 2026