Resampling Methods for Testing a Semiparametric Random Censorship Model |
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Authors: | L. X. ZHU,K. C. YUEN,& N. Y. TANG |
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Affiliation: | University of Hong Kong, Chinese Academy of Sciences |
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Abstract: | This paper presents a goodness-of-fit test for a semiparametric random censorship model proposed by Dikta (1998 ). The test statistic is derived from a model-based process which is asymptotically Gaussian. In addition to test consistency, the proposed test can detect local alternatives distinct n -1/2 from the null hypothesis. Due to the intractability of the asymptotic null distribution of the test statistic, we turn to two resampling approximations. We first use the well-known bootstrap method to approximate critical values of the test. We then introduce a so-called random symmetrization method for carrying out the test. Both methods perform very well with a sample of moderate size. A simulation study shows that the latter possesses better empirical powers and sizes for small samples. |
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Keywords: | bootstrap empirical process Gaussian process random censorship random symmetrization test consistency |
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