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fullROC
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]
[Scholar Profile | Author Map]
All associated links for this package
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 21 Nov. 2024.
Previous versions and publish date:
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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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