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gWQS
View on CRAN: Click
here
Download and install gWQS package within the R console
Install from CRAN:
install.packages("gWQS")
Install from Github:
library("remotes")
install_github("cran/gWQS")
Install by package version:
library("remotes")
install_version("gWQS", "3.0.5")
Attach the package and use:
library("gWQS")
Maintained by
Stefano Renzetti
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2016-10-21
Latest Update: 2023-11-16
Description:
Fits Weighted Quantile Sum (WQS) regression (Carrico et al. (2014) ), a random subset implementation of WQS (Curtin et al. (2019) ), a repeated holdout validation WQS (Tanner et al. (2019) ) and a WQS with 2 indices (Renzetti et al. (2023) ) for continuous, binomial, multinomial, Poisson, quasi-Poisson and negative binomial outcomes.
How to cite:
Stefano Renzetti (2016). gWQS: Generalized Weighted Quantile Sum Regression. R package version 3.0.5, https://cran.r-project.org/web/packages/gWQS. Accessed 03 May. 2025.
Previous versions and publish date:
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imports, suggests or enhances
Complete documentation for gWQS
Functions, R codes and Examples using
the gWQS R package
Some associated functions: main_functions . methods . secondary_functions . tiwqs_data . wqs_data .
Some associated R codes: data.R . gwqs.R . wqs_helpers.R . Full gWQS package functions and examples
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