The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.

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
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

Documentation:

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

Downloads:

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

Linking:

Please use the canonical form https://CRAN.R-project.org/package=wqspt to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.