Significance Tests in Cox Proportional Hazard Model for Survival Times of Complex Survey Data

• 발행기관: 한국자료분석학회
• 저자명: Piljune Moon Kang Mo Jeong
• 간행물 정보: 『Journal of The Korean Data Analysis Society (JKDAS)』Vol.19 No.6, 2881~2890쪽, 전체 10쪽
• 주제분류: 자연과학 > 통계학
• 파일형태: PDF
• 발행일자: 2017.12.31

영문 초록

We consider the Cox PH (proportional hazard) model applied to survival times under complex survey sampling such as cluster sampling. Observations in the same cluster are correlated each other and furthermore they have unequal selection probabilities between clusters. These are the main properties of complex survey data in contrast to the data of simple random sampling. Significance tests for regression coefficients in Cox PH model are based on pseudo partial-likelihood function that incorporates weights of observations. The weight is usually given as the inverse of selection probability of individual unit. The asymptotic distribution of LRT (likelihood ratio test) is not the usual chi-squared distribution but it is given as a linear combination of independent chi-squared random variables. There have been several approaches to approximate the percentage points of asymptotic distribution. We compare the performance of tests and their approximation through a Monte Carlo study.

목차

1. Introduction

2. Pseudo Maximum Likelihood Estimation Using Weighted Partial Likelihood

3. Significance Tests and Approximations to p-values

4. An Empirical Study

5. Concluding Remarks

키워드

Complex sampling Cox PH model Weighted partial likelihood LRT Wald test