qgcompint: Quantile G-Computation Extensions for Effect Measure Modification (original) (raw)
G-computation for a set of time-fixed exposures with quantile-based basis functions, possibly under linearity and homogeneity assumptions. Effect measure modification in this method is a way to assess how the effect of the mixture varies by a binary, categorical or continuous variable. Reference: Alexander P. Keil, Jessie P. Buckley, Katie M. OBrien, Kelly K. Ferguson, Shanshan Zhao, and Alexandra J. White (2019) A quantile-based g-computation approach to addressing the effects of exposure mixtures; <doi:10.1289/EHP5838>.
| Version: | 0.7.0 |
|---|---|
| Depends: | R (≥ 3.5.0) |
| Imports: | qgcomp, arm, survival, future, future.apply, ggplot2, gridExtra |
| Suggests: | knitr, markdown, devtools |
| Published: | 2022-03-22 |
| DOI: | 10.32614/CRAN.package.qgcompint |
| Author: | Alexander Keil [aut, cre] |
| Maintainer: | Alexander Keil |
| BugReports: | https://github.com/alexpkeil1/qgcomp/issues |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: | https://github.com/alexpkeil1/qgcomp/ |
| NeedsCompilation: | no |
| Language: | en-US |
| Materials: | README NEWS |
| CRAN checks: | qgcompint results |
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