Fitting Proportional Odds Survival Models with Random Effects via Binominal HGLMs

• 발행기관: 한국자료분석학회
• 저자명: Il Do Ha
• 간행물 정보: 『Journal of The Korean Data Analysis Society (JKDAS)』Vol.12 No.6, 2953~2962쪽, 전체 10쪽
• 주제분류: 자연과학 > 통계학
• 파일형태: PDF
• 발행일자: 2010.12.30

영문 초록

Recently, survival models with random effects have been widely used for the analysis of correlated survival data. In particular, frailty models(FMs) and proportional odds models (POMs) with random effects are useful. The FMs are based on the assumption of proportional hazards(PH), whereas POMs are not. The POM is a flexible non-PH model and give an interpretation of odds ratio in survival analysis. However, it is usually difficult to fit POMs with random effects because of integration about random effects and censoring. The hierarchical-likelihood for the random-effect POMs can be expressed as that for binominal hierarchical generalized linear models(HGLMs). Thus, in this paper we show how to fit easily the POMs via HGLMs. The proposed method is illustrated using a well-known correlated survival data set.

목차

1. Introduction

2. A classical proportional odds model

3. Fitting proportional odds models with random effects

4. Illustration

5. Discussion

References

키워드

Frailty models H-likelihood Hierarchical generalized linear models Non-proportional hazards Proportional odds models