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wevid

Quantifying Performance of a Binary Classifier Through Weight of Evidence

v0.6.2 · Sep 12, 2019 · GPL-3

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 (2019), <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.

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CRAN incoming feasibility

Maintainer: ‘Marco Colombo <mar.colombo13@gmail.com>’

Package CITATION file contains call(s) to old-style citEntry().  Please
use bibentry() instead.
NOTE r-devel-linux-x86_64-debian-gcc

CRAN incoming feasibility

Maintainer: ‘Marco Colombo <mar.colombo13@gmail.com>’

Package CITATION file contains call(s) to old-style citEntry().  Please
use bibentry() instead.

Check History

NOTE 12 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 10, 2026
NOTE r-devel-linux-x86_64-debian-clang

CRAN incoming feasibility

Maintainer: ‘Marco Colombo <mar.colombo13@gmail.com>’

Package CITATION file contains call(s) to old-style citEntry().  Please
use bibentry() instead.
NOTE r-devel-linux-x86_64-debian-gcc

CRAN incoming feasibility

Maintainer: ‘Marco Colombo <mar.colombo13@gmail.com>’

Package CITATION file contains call(s) to old-style citEntry().  Please
use bibentry() instead.

Dependency Network

Dependencies Reverse dependencies ggplot2 mclust pROC reshape2 zoo wevid

Version History

new 0.6.2 Mar 10, 2026
updated 0.6.2 ← 0.6.1 diff Sep 11, 2019
updated 0.6.1 ← 0.6 diff May 12, 2019
updated 0.6 ← 0.5.2 diff Apr 3, 2019
updated 0.5.2 ← 0.5.1 diff Dec 15, 2018
updated 0.5.1 ← 0.4.2 diff Oct 10, 2018
new 0.4.2 Jun 14, 2018