wqspt

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).

Last 30 days

This package has been downloaded 256 times in the last 30 days. More than a random curiosity, but not quite a blockbuster. Still, it's gaining traction! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 16 times.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Last 365 days

This package has been downloaded 1,928 times in the last 365 days. That's enough downloads to impress a room full of undergrads. A commendable achievement indeed. The day with the most downloads was Mar 08, 2025 with 40 downloads.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.