Regression Analysis of Grouped Survival Data with Application to Breast Cancer Data
Autor: | L. A. Gloeckler, Ross L. Prentice |
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Rok vydání: | 1978 |
Předmět: |
Statistics and Probability
General Immunology and Microbiology Proportional hazards model Applied Mathematics Regression analysis General Medicine medicine.disease General Biochemistry Genetics and Molecular Biology Grouped data Breast cancer Survival function Statistics Covariate Linear regression medicine General Agricultural and Biological Sciences Survival analysis Mathematics |
Zdroj: | Biometrics. 34:57 |
ISSN: | 0006-341X |
Popis: | Use of the proportional hazards regression model (Cox 1972) substantially liberalized the analysis of censored survival data with covariates. Available procedures for estimation of the relative risk parameter, however, do not adequately handle grouped survival data, or large data sets with many tied failure times. The grouped data version of the proportional hazards model is proposed here for such estimation. Asymptotic likelihood results are given, both for the estimation of the regression coefficient and the survivor function. Some special results are given for testing the hypothesis of a zero regression coefficient which leads, for example, to a generalization of the log-rank test for the comparison of several survival curves. Application to breast cancer data, from the National Cancer Institute-sponsored End Results Group, indicates that previously noted race differences in breast cancer survival times are explained to a large extent by differences in disease extent and other demographic characteristics at diagnosis. |
Databáze: | OpenAIRE |
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