Assessment of Diagnostic and Prognostic Markers
Confidence intervals for the AUC (bootstrap)
Confidence intervals for the AUC (empirical variance estimation)
Confidence intervals for the AUC (theoretical variance estimation)
Check confidence level for AUC's confidence intervals
Checks for parameters to compute the confidence intervals for the AUC
Check grid
Checks of diagnosis scenarios
Check of prognosis scenarios under interval censorship
Check of prognosis scenarios under right censorship
Check the method for estimating the predictive model
Check number of bootstrap samples
Check number of CPUs
Check tim
Check the type of scenario (diagnosis/prognosis)
Weighted empirical ROC curve estimator
AUC and confidence intervals
Evolution of the AUCs
Graphical exploratory data analysis
Exploratory data analysis
Predictive model estimation in diagnosis scenarios
Predictive model (naive estimation)
Predictive model in prognosis scenarios (I)
Predictive model in prognosis scenarios (II)
Print sMSROC
Plot of the predictive model
sMS estimator for diagnostic biomarkers
sMS estimator for prognostic biomarkers and interval censoring
sMS estimator for prognostic biomarkers and right censorship
Plot of the sMS ROC curve estimate
sMS ROC curve estimator computation
Variance of the predictive model
Provides estimations of the Receiver Operating Characteristic (ROC) curve and the Area Under the Curve (AUC) based on the two-stages mixed-subjects ROC curve estimator (Diaz-Coto et al. (2020) <doi:10.1515/ijb-2019-0097> and Diaz-Coto et al. (2020) <doi:10.1080/00949655.2020.1736071>).