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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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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.