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fullROC  

Plot Full ROC Curves using Eyewitness Lineup Data
View on CRAN: Click here


Download and install fullROC package within the R console
Install from CRAN:
install.packages("fullROC")

Install from Github:
library("remotes")
install_github("cran/fullROC")

Install by package version:
library("remotes")
install_version("fullROC", "0.1.0")



Attach the package and use:
library("fullROC")
Maintained by
Yueran Yang
[Scholar Profile | Author Map]
First Published: 2021-01-13
Latest Update: 2021-01-13
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. .
How to cite:
Yueran Yang (2021). fullROC: Plot Full ROC Curves using Eyewitness Lineup Data. R package version 0.1.0, https://cran.r-project.org/web/packages/fullROC. Accessed 30 Apr. 2025.
Previous versions and publish date:
No previous versions
Other packages that cited fullROC R package
View fullROC citation profile
Other R packages that fullROC depends, imports, suggests or enhances
Complete documentation for fullROC
Functions, R codes and Examples using the fullROC R package
Some associated functions: auc_boot . auc_ci . id_adj . id_adj_name . id_adj_pos . response_calculate . response_simu . roc_auc . roc_plot . 
Some associated R codes: adjust_id.R . auc_boot.R . roc_auc.R . roc_plot.R . simu_data.R .  Full fullROC package functions and examples
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