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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>.
Getting started
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Package details |
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| Author | Jessica Grembi [aut, cre, cph] (<https://orcid.org/0000-0001-6142-4913>), Elizabeth Rogawski McQuade [ctb] (<https://orcid.org/0000-0002-4942-3747>) |
| Maintainer | Jessica Grembi <jess.grembi@gmail.com> |
| License | GPL-3 |
| Version | 1.0.1 |
| Package repository | View on CRAN |
| Installation |
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