Tests of Calibration in Survival Analysis: Gronnesby-Borgan and D'agostino-Nam Tests

• Activity Number: 392
• Type: Contributed
• Date/Time: Tuesday, August 5, 2014 : 2:00 PM to 3:50 PM
• Sponsor: Biometrics Section
• Author(s): Olga Demler*+ and Nina Paynter and Nancy Cook
• Companies: Brigham & Women's Hospital/Harvard Medical School and Brigham & Women's Hospital and Brigham & Women's Hospital/Harvard Medical School
• Keywords: survival analysis ; calibration ; goodness of fit

Abstract

To access the calibration of a predictive model in a survival analysis setting, several authors have extended the Hosmer and Lemeshow goodness of fit test to survival data. Gronnesby and Borgan developed a test under the assumption of proportional hazards, and D'Agostino and Nam developed a nonparametric test that is applicable in a more general survival setting for data with limited censoring. We analyze the performance of the two tests and show that the Gronnesby-Borgan test attains appropriate size in a variety of settings, whereas the D'Agostino-Nam method has a high Type 1 error when there is more than trivial censoring. Both tests are sensitive to small cell sizes. We develop a modification of the D'Agostino-Nam test to allow for higher censoring rates. We show that this modified D'Agostino-Nam test has appropriate Type 1 error and comparable power to the Gronnesby-Borgan test, and is applicable to settings other than proportional hazards. We also discuss the application to small cell sizes.