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fullROC (version 0.1.0)

Plot Full ROC Curves using Eyewitness Lineup Data

Description

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". , 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. .

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Version

Install

install.packages('fullROC')

Monthly Downloads

160

Version

0.1.0

License

GPL (>= 3)

Maintainer

Yueran Yang

Last Published

January 13th, 2021

Functions in fullROC (0.1.0)

roc_auc

A function to calculate AUC using non-cumulative response rates.
id_adj_pos

Match by position
auc_boot

Bootstrap AUCs
id_adj

Simple adjustment
response_calculate

A function to calculate responses from simulated memory distribution
auc_ci

Bootstrap confidence intervals for AUC
roc_plot

A function to plot ROC curves.
response_simu

Simulate witness responses
id_adj_name

Match by confidence levels