Proceedings of the Korean Statistical Society Conference (한국통계학회:학술대회논문집)
- 2000.11a
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- Pages.193-200
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- 2000
Random Effects Models for Multivariate Survival Data: Hierarchical-Likelihood Approach
- Ha Il Do (Faculty of Information Science, Kyungsan University) ;
- Lee Youngjo (Department of Statistics, Seoul National University) ;
- Song Jae-Kee (Department of Statistics, Kyungpook National University)
- Published : 2000.11.01
Abstract
Modelling the dependence via random effects in censored multivariate survival data has recently received considerable attention in the biomedical literature. The random effects models model not only the conditional survival times but also the conditional hazard rate. Systematic likelihood inference for the models with random effects is possible using Lee and Nelder's (1996) hierarchical-likelihood (h-likelihood). The purpose of this presentation is to introduce Ha et al.'s (2000a,b) inferential methods for the random effects models via the h-likelihood, which provide a conceptually simple, numerically efficient and reliable inferential procedures.
Keywords
- Frailty models;
- Hierarchical-likelihood;
- Marginal likelihood;
- Mixed linear models;
- Multivariate survival data;
- Random effects;
- Restricted maximum likelihood