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 |
| Reference manual: | wqspt.html , wqspt.pdf |
| Vignettes: |
How to use the wqspt package (source, R code) |
| Package source: | wqspt_1.0.2.tar.gz |
| Windows binaries: | r-devel: wqspt_1.0.2.zip, r-release: wqspt_1.0.2.zip, r-oldrel: wqspt_1.0.2.zip |
| macOS binaries: | r-release (arm64): wqspt_1.0.2.tgz, r-oldrel (arm64): wqspt_1.0.2.tgz, r-release (x86_64): wqspt_1.0.2.tgz, r-oldrel (x86_64): wqspt_1.0.2.tgz |
| Old sources: | wqspt archive |
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