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 Alexandra J. White (2019) A quantile-based g-computation approach to addressing the effects of exposure mixtures; <arXiv:1902.04200> [stat.ME].
Version: | 2.0.0 |
Depends: | R (≥ 3.5.0) |
Imports: | arm, future, future.apply, ggplot2, grDevices, grid, gridExtra, pscl, stats, survival |
Suggests: | knitr |
Published: | 2020-01-16 |
Author: | Alexander Keil [aut, cre] |
Maintainer: | Alexander Keil <akeil at unc.edu> |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
NeedsCompilation: | no |
Language: | en-US |
Materials: | README NEWS |
CRAN checks: | qgcomp results |
Reference manual: | qgcomp.pdf |
Vignettes: |
The qgcomp package: g-computation on exposure quantiles |
Package source: | qgcomp_2.0.0.tar.gz |
Windows binaries: | r-devel: qgcomp_2.0.0.zip, r-devel-gcc8: qgcomp_2.0.0.zip, r-release: qgcomp_2.0.0.zip, r-oldrel: qgcomp_2.0.0.zip |
OS X binaries: | r-release: qgcomp_2.0.0.tgz, r-oldrel: qgcomp_2.0.0.tgz |
Old sources: | qgcomp archive |
Please use the canonical form https://CRAN.R-project.org/package=qgcomp to link to this page.