Package: wevid
Type: Package
Title: Quantifying Performance of a Binary Classifier Through Weight of
        Evidence
Version: 0.5.1
Date: 2018-10-11
Authors@R: c(person("Paul", "McKeigue",
                    email="paul.mckeigue@ed.ac.uk", role=c("aut"),
                    comment=c(ORCID="0000-0002-5217-1034")),
             person("Marco", "Colombo",
                    email="m.colombo@ed.ac.uk", role=c("ctb", "cre"),
                    comment=c(ORCID="0000-0001-6672-0623")))
Description: The distributions of the weight of evidence (log Bayes factor) favouring case over noncase status in a test dataset (or test folds generated by cross-validation) can be used to quantify the performance of a diagnostic test (McKeigue (2018), <doi:10.1177/0962280218776989>). The package can be used with any test dataset on which you have observed case-control status and have computed prior and posterior probabilities of case status using a model learned on a training dataset. To quantify how the predictor will behave as a risk stratifier, the quantiles of the distributions of weight of evidence in cases and controls can be calculated and plotted.
Depends: R (>= 2.10)
License: GPL-3
URL:
        http://www.homepages.ed.ac.uk/pmckeigu/preprints/classify/wevidtutorial.html
LazyLoad: yes
Imports: ggplot2, pROC, reshape2, zoo
ByteCompile: TRUE
Encoding: UTF-8
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-10-11 12:03:08 UTC; mcolombo
Author: Paul McKeigue [aut] (<https://orcid.org/0000-0002-5217-1034>),
  Marco Colombo [ctb, cre] (<https://orcid.org/0000-0001-6672-0623>)
Maintainer: Marco Colombo <m.colombo@ed.ac.uk>
Repository: CRAN
Date/Publication: 2018-10-11 12:20:03 UTC
