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qgcomp: Quantile G-Computation (original) (raw)

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: 2.15.2
Depends: R (≥ 3.5.0)
Imports: arm, future, future.apply, generics, ggplot2 (≥ 3.3.0), grDevices, grid, gridExtra, nnet, pscl, stats, survival, tibble
Suggests: broom, devtools, knitr, markdown, MASS, mice
Published: 2023-08-10
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

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