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gWQS: Generalized Weighted Quantile Sum Regression
Fits Weighted Quantile Sum (WQS) regression (Carrico et al. (2014) <doi:10.1007/s13253-014-0180-3>), a random subset implementation of WQS (Curtin et al. (2019) <doi:10.1080/03610918.2019.1577971>), a repeated holdout validation WQS (Tanner et al. (2019) <doi:10.1016/j.mex.2019.11.008>) and a WQS with 2 indices (Renzetti et al. (2023) <doi:10.3389/fpubh.2023.1289579>) for continuous, binomial, multinomial, Poisson, quasi-Poisson and negative binomial outcomes.
Getting started
Browse package contents
Package details |
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| Author | Stefano Renzetti [aut, cre], Paul Curtin [aut], Allan C Just [ctb], Ghalib Bello [ctb], Chris Gennings [aut] |
| Maintainer | Stefano Renzetti <stefano.renzetti88@gmail.com> |
| License | GPL (>= 2) |
| Version | 3.0.5 |
| Package repository | View on CRAN |
| Installation |
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