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Resampling Methods for Testing a Semiparametric Random Censorship Model

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  • L. X. ZHU
  • K. C. YUEN
  • N. Y. TANG

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.

Suggested Citation

  • L. X. Zhu & K. C. Yuen & N. Y. Tang, 2002. "Resampling Methods for Testing a Semiparametric Random Censorship Model," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 29(1), pages 111-123, March.
    • Handle: RePEc:bla:scjsta:v:29:y:2002:i:1:p:111-123
    DOI: 10.1111/1467-9469.00275
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    Cited by:

    1. Cao, Ricardo & Gonzalez-Manteiga, Wenceslao, 2008. "Goodness-of-fit tests for conditional models under censoring and truncation," Journal of Econometrics, Elsevier, vol. 143(1), pages 166-190, March.
    2. Ming Yuan, 2005. "Semiparametric censorship model with covariates," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 14(2), pages 489-514, December.

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