Uses multiple AUCs to select a combination of predictors when the outcome has multiple (ordered) levels and the focus is discriminating one particular level from the others. This method is most naturally applied to settings where the outcome has three levels. (Meisner, A, Parikh, CR, and Kerr, KF (2017) <http://biostats.bepress.com/uwbiostat/paper423/>.)
| Version: | 0.1.0 |
| Imports: | Hmisc |
| Suggests: | MASS |
| Published: | 2018-01-25 |
| DOI: | 10.32614/CRAN.package.multiselect |
| Author: | Allison Meisner |
| Maintainer: | Allison Meisner <allison.meisner at gmail.com> |
| License: | GPL-2 |
| NeedsCompilation: | no |
| CRAN checks: | multiselect results |
| Reference manual: | multiselect.html , multiselect.pdf |
| Package source: | multiselect_0.1.0.tar.gz |
| Windows binaries: | r-devel: multiselect_0.1.0.zip, r-release: multiselect_0.1.0.zip, r-oldrel: multiselect_0.1.0.zip |
| macOS binaries: | r-release (arm64): multiselect_0.1.0.tgz, r-oldrel (arm64): multiselect_0.1.0.tgz, r-release (x86_64): multiselect_0.1.0.tgz, r-oldrel (x86_64): multiselect_0.1.0.tgz |
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