wqspt: Permutation Test for Weighted Quantile Sum Regression

Implements a permutation test method for the weighted quantile sum (WQS) regression, building off the 'gWQS' package (Renzetti et al. (2021) <https://CRAN.R-project.org/package=gWQS>). Weighted quantile sum regression is a statistical technique to evaluate the effect of complex exposure mixtures on an outcome (Carrico et al. (2015) <doi:10.1007/s13253-014-0180-3>). The model features a statistical power and Type I error (i.e., false positive) rate trade-off, as there is a machine learning step to determine the weights that optimize the linear model fit. This package provides an alternative method based on a permutation test that should reliably allow for both high power and low false positive rate when utilizing WQS regression (Day et al. (2022) <doi:10.1289/EHP10570>).

Version: 1.0.1
Depends: R (≥ 3.5.0)
Imports: rlang, gWQS, pbapply, ggplot2, mvtnorm, viridis, extraDistr, cowplot, methods
Suggests: rmarkdown, knitr, testthat (≥ 3.0.0)
Published: 2023-03-06
DOI: 10.32614/CRAN.package.wqspt
Author: Drew Day [aut, cre], James Peng [aut], Adam Szpiro [aut]
Maintainer: Drew Day <Drew.Day at seattlechildrens.org>
License: GPL-3
NeedsCompilation: no
Materials: README
CRAN checks: wqspt results


Reference manual: wqspt.pdf
Vignettes: How to use the wqspt package


Package source: wqspt_1.0.1.tar.gz
Windows binaries: r-devel: wqspt_1.0.1.zip, r-release: wqspt_1.0.1.zip, r-oldrel: wqspt_1.0.1.zip
macOS binaries: r-release (arm64): wqspt_1.0.1.tgz, r-oldrel (arm64): wqspt_1.0.1.tgz, r-release (x86_64): wqspt_1.0.1.tgz, r-oldrel (x86_64): wqspt_1.0.1.tgz


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