Implements a permutation test method for the weighted quantile sum (WQS) regression, building off the 'gWQS' package (Renzetti et al. <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: 1.0.2 Depends: R (≥ 3.5.0) Imports: rlang, gWQS, pbapply, ggplot2, mvtnorm, viridis, extraDistr, cowplot, methods, MASS, car, future, future.apply, pscl, reshape2, nnet Suggests: rmarkdown, knitr, testthat (≥ 3.0.0) Published: 2025-03-05 DOI: 10.32614/CRAN.package.wqspt Author: Drew Day [aut, cre], James Peng [aut], Adam Szpiro [aut] Maintainer: Drew Day <dday612 at gmail.com> License: GPL-3 NeedsCompilation: no Materials: README, NEWS CRAN checks: wqspt results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=wqspt to link to this page.
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