Package: riskCommunicator 1.0.1

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>.

Authors:Jessica Grembi [aut, cre, cph], Elizabeth Rogawski McQuade [ctb]

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Bug tracker:https://github.com/jgrembi/riskcommunicator/issues

On CRAN:

2 exports 4 stars 1.33 score 67 dependencies 1 mentions 14 scripts 283 downloads

Last updated 2 years agofrom:548afe7bb2. Checks:OK: 7. Indexed: yes.

Exports:gComppointEstimate

Dependencies:abindbackportsbootbroomcarcarDataclicolorspacecorrplotcowplotcpp11DerivdoBydplyrfansifarvergenericsggplot2ggpubrggrepelggsciggsignifgluegridExtragtableisobandlabelinglatticelifecyclelme4magrittrMASSMatrixMatrixModelsmgcvmicrobenchmarkminqamodelrmunsellnlmenloptrnnetnumDerivpbkrtestpillarpkgconfigpolynompurrrquantregR6RColorBrewerRcppRcppEigenrlangrstatixscalesSparseMstringistringrsurvivaltibbletidyrtidyselectutf8vctrsviridisLitewithr