Journal of the Korean Data and Information Science Society

The Korean Data and Information Science Society (한국데이터정보과학회)
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On prediction of random effects in log-normal frailty models

  • Ha, Il-Do (Department of Asset Management, Daegu Haany University) ;
  • Cho, Geon-Ho (Department of Asset Management, Daegu Haany University)
  • Published : 2009.01.31
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Abstract

Frailty models are useful for the analysis of correlated and/or heterogeneous survival data. However, the inferences of fixed parameters, rather than random effects, have been mainly studied. The prediction (or estimation) of random effects is also practically useful to investigate the heterogeneity of the hospital or patient effects. In this paper we propose how to extend the prediction method for random effects in HGLMs (hierarchical generalized linear models) to log-normal semiparametric frailty models with nonparametric baseline hazard. The proposed method is demonstrated by a simulation study.

Keywords

References

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