Permutation Test for Weighted Quantile Sum Regression R package wqspt version 1.0.2 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>). Software 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) Drew Day <dday612@gmail.com> Comprehensive R Archive Network (CRAN) Drew Day [aut, cre], James Peng [aut], Adam Szpiro [aut] GPL-3 2025-03-05 application/tgz https://CRAN.R-project.org/package=wqspt doi:10.32614/CRAN.package.wqspt