Other packages > Find by keyword >

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]
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 07 Oct. 2026.
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
Downloads during the last 30 days

Today's Hot Picks in Authors and Packages

blandr  
Bland-Altman Method Comparison
Carries out Bland Altman analyses (also known as a Tukey mean-difference plot) as described by JM B ...
Download / Learn more Package Citations See dependency  
nextGenShinyApps  
Craft Exceptional 'R Shiny' Applications and Dashboards with Novel Responsive Tools
Nove responsive tools for designing and developing 'Shiny' dashboards and applications. The scripts ...
Download / Learn more Package Citations See dependency  
ggTimeSeries  
Time Series Visualisations Using the Grammar of Graphics
Provides additional display mediums for time series visualisations. ...
Download / Learn more Package Citations See dependency  
skewlmm  
Scale Mixture of Skew-Normal Linear Mixed Models
It fits scale mixture of skew-normal linear mixed models using an expectation–maximization (EM) ty ...
Download / Learn more Package Citations See dependency  
PairedData  
Paired Data Analysis
Many datasets and a set of graphics (based on ggplot2), statistics, effect sizes and hypothesis test ...
Download / Learn more Package Citations See dependency  
plaqr  
Partially Linear Additive Quantile Regression
Estimation, prediction, thresholding, transformation, and plotting for partially linear additive qua ...
Download / Learn more Package Citations See dependency  

28,905

R Packages

247,686

Dependencies

76,495

Author Associations

28,906

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA