Most ROC curve plots obscure the cutoff values and inhibit interpretation and comparison of multiple curves. This attempts to address those shortcomings by providing plotting and interactive tools. Functions are provided to generate an interactive ROC curve plot for web use, and print versions. A Shiny application implementing the functions is also included.
|Author||Michael C Sachs|
|Date of publication||2016-02-05 21:48:08|
|Maintainer||Michael C Sachs <email@example.com>|
|License||MIT + file LICENSE|
calc_auc: Calculate the Area under the ROC curve
calculate_multi_roc: Calculate the Empirical ROC curves for multiple biomarkers
calculate_roc: Calculate the Empirical ROC curve
direct_label: Add direct labels to a ROC plot
export_interactive_roc: Generate svg code for an ROC curve object
geom_roc: Empirical Receiver Operating Characteristic Curve
geom_rocci: Confidence regions for the ROC curve
ggroc: Plot an ROC curve
melt_roc: Transform biomarkers stored as wide to long
multi_ggroc: Plot multiple ROC curves
plot_interactive_roc: Generate a standalone html document displaying an interactive...
plot_journal_roc: Plot an ROC curve for use in print
plotROC: Tools for plotting ROC Curves
shiny_plotROC: Start the plotROC Shiny app
stat_roc: Calculate the empirical Receiver Operating Characteristic...
stat_rocci: Calculate confidence regions for the empirical ROC curve
style_roc: Add guides and annotations to a ROC plot
verify_d: Check that D is suitable for using as binary disease status