NONPARAMETRIC ANALYSIS OF CHANGES IN HAZARD RATES FOR CENSORED SURVIVAL-DATA - AN ALTERNATIVE TO CHANGE-POINT MODELS
成果类型：
Article
署名作者：
MULLER, HG; WANG, JL
刊物名称：
BIOMETRIKA
ISSN/ISSBN：
0006-3444
DOI：
10.2307/2336808
发表日期：
1990
页码：
305314
关键词：
摘要：
As a nonparametric estimator for the point of the most rapid change of a hazard rate we propose the location of an extremum of a nonparametric estimate of the derivative, or equivalently, of a zero of a nonparametric estimate of the second derivative. Using the kernel method for the nonparametric estimation of derivatives of the hazard rate, the asymptotic local limiting distribution and uniform consistency are applied to prove consistency and to find the limiting distribution of these estimators under random censoring and to construct confidence intervals both for the derivatives of the hazard rate and for the point of most rapid change. An application to leukaemia data illustrates this concept, and we discuss its relations to change-point modelling. The Monte Carlo method is used to assess the reliability of finite sample analyses, and in particular of the given example.