Abstract Details
Activity Number:
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392
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Type:
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Contributed
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Date/Time:
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Tuesday, August 5, 2014 : 2:00 PM to 3:50 PM
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Sponsor:
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Biometrics Section
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Abstract #312476
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Title:
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Tests of Calibration in Survival Analysis: Gronnesby-Borgan and D'agostino-Nam Tests
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Author(s):
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Olga Demler*+ and Nina Paynter and Nancy Cook
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Companies:
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Brigham & Women's Hospital/Harvard Medical School and Brigham & Women's Hospital and Brigham & Women's Hospital/Harvard Medical School
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Keywords:
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survival analysis ;
calibration ;
goodness of fit
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Abstract:
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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.
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Authors who are presenting talks have a * after their name.
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