Communications for Statistical Applications and Methods

The Korean Statistical Society (한국통계학회)
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Genetic Mixed Effects Models for Twin Survival Data

  • Ha, Il-Do (Department of Asset Management, Daegu Haany University) ;
  • Noh, Maengseok (Department of Statistics, Seoul National University) ;
  • Yoon, Sangchul (Department of Compuer and Information Science, Daegu Haany University)
  • Published : 2005.12.01
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Abstract

Twin studies are one of the most widely used methods for quantifying the influence of genetic and environmental factors on some traits such as a life span or a disease. In this paper we propose a genetic mixed linear model for twin survival time data, which allows us to separate the genetic component from the environmental component. Inferences are based upon the hierarchical likelihood (h-likelihood), which provides a statistically efficient and simple unified framework for various random-effect models. We also propose a simple and fast computation method for analyzing a large data set on twin survival study. The new method is illustrated to the survival data in Swedish Twin Registry. A simulation study is carried out to evaluate the performance.

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References

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