Comprehensive evaluation of biomarker predictive performance over time using time-dependent ROC analysis. Supports multiple ROC estimation methods and provides clinical interpretation of results.
Details
This analysis provides time-dependent ROC curve analysis with:
Multiple estimation methods (incident, cumulative, static)
Bootstrap confidence intervals for robust inference
Optimal cutoff calculation using Youden index
Comprehensive visualization (ROC curves and AUC over time)
Clinical interpretation and performance assessment
Model comparison capabilities
Super classes
jmvcore::Analysis -> ClinicoPath::timerocBase -> timerocClass
Methods
Inherited methods
jmvcore::Analysis$.createImage()jmvcore::Analysis$.createImages()jmvcore::Analysis$.createPlotObject()jmvcore::Analysis$.load()jmvcore::Analysis$.render()jmvcore::Analysis$.save()jmvcore::Analysis$.savePart()jmvcore::Analysis$.setCheckpoint()jmvcore::Analysis$.setParent()jmvcore::Analysis$.setReadDatasetHeaderSource()jmvcore::Analysis$.setReadDatasetSource()jmvcore::Analysis$.setResourcesPathSource()jmvcore::Analysis$.setStatePathSource()jmvcore::Analysis$addAddon()jmvcore::Analysis$asProtoBuf()jmvcore::Analysis$asSource()jmvcore::Analysis$check()jmvcore::Analysis$init()jmvcore::Analysis$optionsChangedHandler()jmvcore::Analysis$postInit()jmvcore::Analysis$print()jmvcore::Analysis$readDataset()jmvcore::Analysis$run()jmvcore::Analysis$serialize()jmvcore::Analysis$setError()jmvcore::Analysis$setStatus()jmvcore::Analysis$translate()ClinicoPath::timerocBase$initialize()