fullROC: Plot Full ROC Curves using Eyewitness Lineup Data

Enable researchers to adjust identification rates using the 1/(lineup size) method, generate the full receiver operating characteristic (ROC) curves, and statistically compare the area under the curves (AUC). References: Yueran Yang & Andrew Smith. (2020). "fullROC: An R package for generating and analyzing eyewitness-lineup ROC curves". <doi:10.13140/RG.2.2.20415.94885/1> , Andrew Smith, Yueran Yang, & Gary Wells. (2020). "Distinguishing between investigator discriminability and eyewitness discriminability: A method for creating full receiver operating characteristic curves of lineup identification performance". Perspectives on Psychological Science, 15(3), 589-607. <doi:10.1177/1745691620902426>.

Version:	0.1.0
Imports:	stats, graphics
Published:	2021-01-13
DOI:	10.32614/CRAN.package.fullROC
Author:	Yueran Yang [aut, cre]
Maintainer:	Yueran Yang <yuerany at unr.edu>
BugReports:	https://github.com/yuerany/fullROC/issues
License:	GPL (≥ 3)
NeedsCompilation:	no
Language:	en-US
CRAN checks:	fullROC results

Documentation:

Reference manual:

fullROC.pdf

Downloads:

Package source:	fullROC_0.1.0.tar.gz
Windows binaries:	r-devel: fullROC_0.1.0.zip, r-release: fullROC_0.1.0.zip, r-oldrel: fullROC_0.1.0.zip
macOS binaries:	r-release (arm64): fullROC_0.1.0.tgz, r-oldrel (arm64): fullROC_0.1.0.tgz, r-release (x86_64): fullROC_0.1.0.tgz, r-oldrel (x86_64): fullROC_0.1.0.tgz

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