Efron-type measures of prediction error for survival analysis.
Estimates of the prediction error play an important role in the development of statistical methods and models, and in their applications. We adapt the resampling tools of Efron and Tibshirani (1997, Journal of the American Statistical Association92, 548-560) to survival analysis with right-censored event times. We find that flexible rules, like artificial neural nets, classification and regression trees, or regression splines can be assessed, and compared to less flexible rules in the same data where they are developed. The methods are illustrated with data from a breast cancer trial.
Gerds
Thomas A
TA
Institute of Medical Biometry and Medical Informatics, University of Freiburg, Stefan-Meier-Strasse 26, D-79104 Freiburg, Germany. gerds@fdm.uni-freiburg.de
Schumacher
Martin
M
D000465:Algorithms; D001943:Breast Neoplasms / Q000401:mortality*; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D006801:Humans; D015994:Incidence; D008954:Models, Biological; D015233:Models, Statistical; D015203:Reproducibility of Results; D018570:Risk Assessment / Q000379:methods*; D012307:Risk Factors; D012680:Sensitivity and Specificity; D016019:Survival Analysis; D015996:Survival Rate