qgcomp: Quantile G-Computation
G-computation for a set of time-fixed exposures with
quantile-based basis functions, possibly under linearity and
homogeneity assumptions. This approach estimates a regression line
corresponding to the expected change in the outcome (on the link
basis) given a simultaneous increase in the quantile-based category
for all exposures. Works with continuous, binary, and right-censored
time-to-event outcomes. 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: |
2.16.4 |
| Depends: |
R (≥ 3.5.0) |
| Imports: |
arm, future, future.apply, generics, ggplot2 (≥ 3.3.0), grDevices, grid, gridExtra, nnet, numDeriv, pscl, rootSolve, stats, survival, tibble |
| Suggests: |
broom, devtools, knitr, markdown, MASS, mice |
| Published: |
2025-01-22 |
| DOI: |
10.32614/CRAN.package.qgcomp |
| Author: |
Alexander Keil [aut, cre] |
| Maintainer: |
Alexander Keil <alex.keil at nih.gov> |
| 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: |
qgcomp results |
Documentation:
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Reverse dependencies:
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