Likelihood Ratio-Based Confidence Intervals in Survival Analysis
作者:
S.A. Murphy,
期刊:
Journal of the American Statistical Association
(Taylor Available online 1995)
卷期:
Volume 90,
issue 432
页码: 1399-1405
ISSN:0162-1459
年代: 1995
DOI:10.1080/01621459.1995.10476645
出版商: Taylor & Francis Group
关键词: Infinite-dimensional nuisance parameter;Nonparametric model
数据来源: Taylor
摘要:
Confidence intervals for the survival function and the cumulative hazard function are considered. These confidence intervals are based on an inversion of the likelihood ratio statistic. To do this, two extensions of the likelihood, each of which yields meaningful likelihood ratio hypothesis tests and subsequent confidence intervals, are considered. The choice of the best extension is difficult. In the failure time setting, the binomial extension is best in constructing confidence intervals concerning the survival function and the Poisson extension is best in constructing confidence intervals concerning the cumulative hazard. Simulations indicate that these two methods perform as well as or better than competitors based on the asymptotic normality of the estimator.
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