Package: wqspt
Title: Permutation Test for Weighted Quantile Sum Regression
Version: 1.0.1
Author: Drew Day [aut, cre],
  James Peng [aut],
  Adam Szpiro [aut]
Maintainer: Drew Day <Drew.Day@seattlechildrens.org>
Authors@R: c(
    person("Drew", "Day", email = "Drew.Day@seattlechildrens.org", role = c("aut", "cre")),
    person("James", "Peng", email = "jpspeng@uw.edu", role = "aut"),
    person("Adam", "Szpiro", email = "aszpiro@uw.edu", role = "aut"))
Description: 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>).
License: GPL-3
Encoding: UTF-8
RoxygenNote: 7.2.1
Imports: rlang, gWQS, pbapply, ggplot2, mvtnorm, viridis, extraDistr,
        cowplot, methods
Suggests: rmarkdown, knitr, testthat (>= 3.0.0)
VignetteBuilder: knitr
Config/testthat/edition: 3
NeedsCompilation: no
Packaged: 2023-03-04 00:08:30 UTC; dday
Depends: R (>= 3.5.0)
Repository: CRAN
Date/Publication: 2023-03-06 14:00:02 UTC
Built: R 4.2.0; ; 2023-07-11 02:14:48 UTC; unix
