Two Ways of Modelling Multilevel Survival Data

• 발행기관: 한국자료분석학회
• 저자명: 하일도(Il Do Ha) 조건호(Geon-Ho Cho)
• 간행물 정보: 『Journal of The Korean Data Analysis Society (JKDAS)』Vol.7 No.1, 33~39쪽, 전체 7쪽
• 주제분류: 자연과학 > 통계학
• 파일형태: PDF
• 발행일자: 2005.02.28

영문 초록

Multilevel survival data with nested structures can be modelled by random-effect models such as multilevel mixed linear models and multilevel frailty models. We show how to analyze the well-known chronic granulomatous disease data, which comprise recurrent infection times of patients from different hospitals, using both types of multilevel survival models and discuss their relative merits. Inferences are based upon the hierarchical likelihood, which provides a simple unified framework and a numerically efficient fitting algorithm for various random-effect models.

목차

1. Introduction

2. The CGD Data

3. Multilevel Survival Models

4. Discussion

References

키워드

Hierarchical likelihood Multilevel frailty models Multilevel mixed linear models Multilevel survival data.