Multivariate Survival Analysis

  • John P. Klein
  • Melvin L. Moeschberger
Part of the Statistics for Biology and Health book series (SBH)


In the previous chapters of this book, we have examined a variety of techniques for analyzing survival data. With few exceptions, these techniques are based on the assumption that the survival times of distinct individuals are independent of each other. Although this assumption may be valid in many experimental settings, it may be suspect in others. For example, we may be making inferences about survival in a sample of siblings or litter mates who share a common genetic makeup, or we may be studying survival in a sample of married couples who share a common, unmeasured, environment. A third example is where we are studying the times to occurrence of different nonlethal diseases within the same individual. In each of these situations, it is quite probable that there is some association within groups of survival times in the sample.


Multivariate Survival Analysis Frailty Model Partial Likelihood Marginal Model Litter Mate 
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Copyright information

© Springer Science+Business Media New York 1997

Authors and Affiliations

  • John P. Klein
    • 1
  • Melvin L. Moeschberger
    • 2
  1. 1.Division of BiostatisticsMedical College of WisconsinMilwaukeeUSA
  2. 2.School of Public Health, Division of Epidemiology and BiometricsThe Ohio State University Medical CenterColumbusUSA

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