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. 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: 1.0.0
Depends: ggplot2 (≥ 2.5), grid, gridExtra, R (≥ 3.0), stats (≥ 3.0)
Suggests: knitr (≥ 1.0)
Published: 2019-03-02
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

Downloads:

Reference manual: qgcomp.pdf
Vignettes: The qgcomp package: g-computation on exposure quantiles
Package source: qgcomp_1.0.0.tar.gz
Windows binaries: r-devel: qgcomp_1.0.0.zip, r-release: qgcomp_1.0.0.zip, r-oldrel: qgcomp_1.0.0.zip
OS X binaries: r-release: qgcomp_1.0.0.tgz, r-oldrel: qgcomp_1.0.0.tgz

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