Fits weighted quantile sum (WQS) regressions for one or more chemical groups with continuous or binary outcomes. Wheeler D, Czarnota J.(2016) <doi:10.1289/isee.2016.4698>.

Grouped Weighted Quantile Sum Regression

Rsolnp, glm2, stats, graphics, MASS, rjags

person("Ludvig Renbo", "Olsen", email = "r-pkgs@ludvigolsen.dk", role = c("aut", "cre"))
Subsetting methods for balanced cross-validation, time series windowing,
and general grouping and splitting of data.
ggplot2, knitr, rmarkdown, tidyr, broom, testthat, lmerTest,
hydroGOF

Methods for dividing data into groups.
Create balanced partitions and cross-validation folds.
Perform time series windowing and general grouping and splitting of data.
Balance existing groups with up- and downsampling.

ggplot2, knitr, rmarkdown, tidyr, broom, testthat, lmerTest,
hydroGOF, covr

broom, covr, ggplot2, hydroGOF, knitr, lmerTest, rmarkdown,
testthat, tidyr, xpectr (>= 0.1.1)

broom, covr, ggplot2, hydroGOF, knitr, lmerTest, rmarkdown,
testthat, tidyr, xpectr (>= 0.3.0)

broom, covr, ggplot2, hydroGOF, knitr, lmerTest, rmarkdown,
testthat, tidyr, xpectr (>= 0.4.0)

checkmate (>= 2.0.0), dplyr (>= 0.8.4), numbers (>= 0.7-5),
lifecycle, plyr (>= 1.8.5), purrr, rlang (>= 0.4.4), stats,
tibble (>= 2.1.3), tidyr, utils
broom, covr, ggplot2, hydroGOF, knitr, lmerTest, rmarkdown,
testthat, xpectr (>= 0.4.0)

Methods for dividing data into groups.
Create balanced partitions and cross-validation folds.
Perform time series windowing and general grouping and splitting of data.
Balance existing groups with up- and downsampling or collapse them to fewer groups.

broom, covr, ggplot2, hydroGOF, knitr, lmerTest, rmarkdown,
testthat, xpectr (>= 0.4.1)

broom, covr, ggplot2, knitr, lmerTest, rmarkdown, testthat,
xpectr (>= 0.4.1)

Regression Analysis of Grouped and Coarse Data
Dimitris Rizopoulos <dimitris.rizopoulos@med.kuleuven.be> and Spyridoula Tsonaka <spyridoula.tsonaka@med.kuleuven.be>
Regression models for grouped and coarse data, under the Coarsened At Random assumption.