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 | |
| No Results! | ||
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Details
| 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 |
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