Package: wevid
Type: Package
Title: Quantifying Performance of a Binary Classifier Through Weight of
        Evidence
Version: 0.4.2
Date: 2018-06-15
Authors@R: c(person("Paul", "McKeigue",
                    email="paul.mckeigue@ed.ac.uk", role=c("aut")),
             person("Marco", "Colombo",
                    email="m.colombo@ed.ac.uk", role=c("ctb", "cre")))
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 P., Quantifying performance of a diagnostic test as the expected information for discrimination: relation to the C-statistic. Statistical Methods for Medical Research 2018, in press). 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
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-06-15 10:37:58 UTC; marco
Author: Paul McKeigue [aut],
  Marco Colombo [ctb, cre]
Maintainer: Marco Colombo <m.colombo@ed.ac.uk>
Repository: CRAN
Date/Publication: 2018-06-15 11:17:55 UTC
