fullROC v0.1.0


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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>.

Functions in fullROC

Name Description
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
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Type Package
BugReports https://github.com/yuerany/fullROC/issues
Language en-US
License GPL (>= 3)
Encoding UTF-8
LazyData true
RoxygenNote 7.1.1
NeedsCompilation no
Packaged 2021-01-09 00:56:52 UTC; yueran
Repository CRAN
Date/Publication 2021-01-13 11:50:10 UTC
imports graphics , stats

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