Incident/Dynamic (I/D) ROC curve, AUC and integrated AUC (iAUC) estimation of censored survival data

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Description

This is Mayo PBC data as obtained from the website: http://lib.stat.cmu.edu/datasets/pbc

Format

A data frame with 418 observations and 20 variables: id (patient id), fudays (follow-up days, number of days between registration and the earlier of death, transplantation, or study analysis time in July, 1986), status (survival status), drug (1 = D-penicillamine, 2 = placebo) age (age in days), sex (0 = male, 1 = female), ascites (presence of asictes: 0=no 1=yes), hepatom (presence of hepatomegaly: 0=no 1=yes), spiders (presence of spiders: 0=no 1=yes), edema (presence of edema: 0=no edema and no diuretic therapy for edema; .5 = edema present without diuretics, or edema resolved by diuretics; 1 = edema despite diuretic therapy), bili (serum bilirubin in mg/dl), chol (serum cholesterol in mg/dl), albumin (albumin in gm/dl), copper (urine copper in ug/day), alkphos (alkaline phosphatase in U/liter), sgot (SGOT in U/ml), trig (triglicerides in mg/dl), platelet (platelets per cubic ml / 1000), protime (prothrombin time in seconds), stage (histologic stage of disease)

Author(s)

Patrick J. Heagerty

References

Heagerty, P.J., Zheng Y. (2005) Survival Model Predictive Accuracy and ROC curves Biometrics, 61, 92 – 105

Examples

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library(MASS)
data(VA)
## need to order the data in ascending order of survival time
new.VA=VA[order(VA$stime),]
risket.VA=riskset(new.VA)