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Covariance Analysis of Censored Survival Data Using Log-Linear Analysis Techniques
Nan Laird and Donald Olivier
Journal of the American Statistical Association
Vol. 76, No. 374 (Jun., 1981), pp. 231-240
Stable URL: http://www.jstor.org/stable/2287816
Page Count: 10
You can always find the topics here!Topics: Statistical models, Statistics, Censorship, Modeling, Censored data, Life tables, Maximum likelihood estimators, Parametric models, Musical intervals, Covariance
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This paper unites two different fields, survival and contingency table analysis, in a single analytical framework based on the log-linear model. We demonstrate that many currently popular approaches to modeling survival data, including the approaches of Glasser (1967), Cox (1972), Breslow (1972, 1974), and Holford (1976), can be handled by using existing computer packages developed for the log-linear analysis of contingency table data. More important, we demonstrate that the log-linear modeling system used to characterize counted data structures directly characterizes survival data as well. Counted data methodologies for testing and estimation are also applicable here. Much of the theoretical basis for this work has been independently derived by Holford (1980) and Aitkin and Clayton (1980). The emphasis in this paper is not to develop new methodologies, but rather to present new uses and interpretations for already familiar methodologies.
Journal of the American Statistical Association © 1981 American Statistical Association