gfoRmula: Parametric G-Formula
Implements the non-iterative conditional expectation (NICE) algorithm of the g-formula algorithm (Robins (1986) <doi:10.1016/0270-0255(86)90088-6>, Hernán and Robins (2024, ISBN:9781420076165)). The g-formula can estimate an outcome's counterfactual mean or risk under hypothetical treatment strategies (interventions) when there is sufficient information on time-varying treatments and confounders. This package can be used for discrete or continuous time-varying treatments and for failure time outcomes or continuous/binary end of follow-up outcomes. The package can handle a random measurement/visit process and a priori knowledge of the data structure, as well as censoring (e.g., by loss to follow-up) and two options for handling competing events for failure time outcomes. Interventions can be flexibly specified, both as interventions on a single treatment or as joint interventions on multiple treatments. See McGrath et al. (2020) <doi:10.1016/j.patter.2020.100008> for a guide on how to use the package.
| Version: | 1.1.1 |
| Depends: | R (≥ 3.5.0) |
| Imports: | data.table, ggplot2, ggpubr, grDevices, nnet, parallel, progress, stats, stringr, survival, truncnorm, truncreg, utils |
| Suggests: | Hmisc, knitr, randomForest, rmarkdown, testthat (≥ 3.0.0) |
| Published: | 2025-03-24 |
| DOI: | 10.32614/CRAN.package.gfoRmula |
| Author: | Victoria Lin [aut] (V. Lin and S. McGrath made equal contributions),
Sean McGrath 
[aut, cre] (V. Lin and S. McGrath made equal contributions),
Zilu Zhang [aut],
Roger W. Logan [aut],
Lucia C. Petito [aut],
Jing Li [aut],
McGee Emma [aut],
Cheng Carrie [aut],
Jessica G. Young
[aut] (M.A. Hernán and J.G. Young made equal contributions),
Miguel A. Hernán [aut] (M.A. Hernán and J.G. Young made equal
contributions),
2019 The President and Fellows of Harvard College [cph] |
| Maintainer: | Sean McGrath <sean.mcgrath514 at gmail.com> |
| BugReports: | https://github.com/CausalInference/gfoRmula/issues |
| License: | GPL-3 |
| URL: | https://github.com/CausalInference/gfoRmula, https://doi.org/10.1016/j.patter.2020.100008 |
| NeedsCompilation: | no |
| Materials: | README, NEWS |
| In views: | CausalInference |
| CRAN checks: | gfoRmula results |
Documentation:
| Reference manual: | gfoRmula.html , gfoRmula.pdf |
| Vignettes: |
Using Custom Outcome Models in gfoRmula (source, R code) A Simplified Approach for Specifying Interventions in gfoRmula (source, R code) |
Downloads:
| Package source: | gfoRmula_1.1.1.tar.gz |
| Windows binaries: | r-devel: gfoRmula_1.1.1.zip, r-release: gfoRmula_1.1.1.zip, r-oldrel: gfoRmula_1.1.1.zip |
| macOS binaries: | r-release (arm64): gfoRmula_1.1.1.tgz, r-oldrel (arm64): gfoRmula_1.1.1.tgz, r-release (x86_64): gfoRmula_1.1.1.tgz, r-oldrel (x86_64): gfoRmula_1.1.1.tgz |
| Old sources: | gfoRmula archive |
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