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Version 1.22: * Addition of ggcontribute graph * Changed from geom_line to geom_step for the ROC plot (better data representation) * Bug fixes
Version 1.11: * Made NRI metrics for models optional (use NRI_return = TRUE) * Changed behavior so “x2 = NULL” is possible for CI.raplot * Bug fixes
Version 1.10: * Addition of ROC plot * Calibration plot now uses continuous curves (old format available as ggcalibrate_original()) * Addition of precision recall curves * All plots can be for one or two models
Version 1.03: * Major changes allowing logistic regression models from glm (stats) and lrm (rms) * Added Risk Assessment Plot, calibration plot and decision curve outputs * Output functions now return lists with metrics for each bootstrap sample * CI.classNRI produces confusion matrices for events and non-events separately * Bootstrapping used for confidence intervals
The raptools package began as MATLAB code in 2012 following the publication of “New Metrics for Assessing Diagnostic Potential of Candidate Biomarkers” (Clinical Journal of the American Society of Nephrology, 2012). The package provides comprehensive tools for assessing the comparative performance of logistic regression models, particularly in the context of biomarker evaluation and clinical prediction model improvement.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.