Efficient rank tests for semiparametric competing risk models
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- 作者：Jan Beyersmann ; Arnold Janssen and Claus-Dieter Mayer
- 关键词：Semiparametric competing risk model ; Rank tests ; Likelihood ratio type tests ; Asymptotic efficiency
- 刊名：Metrika
- 出版时间：July 2004
- 出版年：2004
- 期刊代码：111_0026-1335
- 类别：mat
- 卷：60
- 期：1
- 页码：73-91
- 数据来源：sp
摘要
We consider a semiparametric competing risk model given by k independent survival times. The paper offers an asymptotic treatment of tests for the semiparametric null hypothesis of equality of the underlying risks. It turns out that modified rank tests are asymptotically efficient for certain semiparametric submodels, where the baseline hazard is a nuisance parameter. In addition, the asymptotic relative efficiency of the present tests is derived. A comparison of asymptotic power functions can then be used to classify various tests proposed earlier in the literature. For instance a chi-square type test is efficient for proportional hazards. Data driven tests of likelihood ratio type are proposed for cones of alternatives. We will consider certain stochastically increasing alternatives as a special example. The paper shows how the concept of local asymptotic normality of Le Cam works for hazard oriented models.