Regression Analysis of Grouped Survival Data with Application to Breast Cancer Data

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ID: 294568
1978
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Abstract
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.
Reference Key
openalex_W1994670953 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Ross L. Prentice, Lynn Ann Gloeckler
Journal biometrics
Year 1978
DOI
10.2307/2529588
URL
https://doi.org/10.2307/2529588
Keywords Keywords not found

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