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Goodness-of-fit testing in interval censoring case 1

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  • Koul, Hira L.
  • Yi, Tingting

Abstract

In the interval censoring case 1, an event occurrence time is unobservable, but one observes an inspection time and whether the event has occurred prior to this time or not. The focus here is to provide tests of goodness-of-fit hypothesis pertaining to the distribution of the event occurrence time. The proposed tests are based on certain marked empirical processes for testing a simple hypothesis and the Stute-Thies-Zhu transformation of such a process for fitting a parametric family of distributions. These tests are asymptotically distribution-free, consistent against a large class of fixed alternatives and have nontrivial asymptotic power against a large class of local alternatives. A simulation study is included to exhibit the finite sample level preservation and power behavior.

Suggested Citation

  • Koul, Hira L. & Yi, Tingting, 2006. "Goodness-of-fit testing in interval censoring case 1," Statistics & Probability Letters, Elsevier, vol. 76(7), pages 709-718, April.
    • Handle: RePEc:eee:stapro:v:76:y:2006:i:7:p:709-718
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    References listed on IDEAS

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    1. Ian Diamond & John McDonald & Iqbal Shah, 1986. "Proportional hazards models for current status data: Application to the study of differentials in age at weaning in Pakistan," Demography, Springer;Population Association of America (PAA), vol. 23(4), pages 607-620, November.
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    Cited by:

    1. Dikta, Gerhard & Subramanian, Sundarraman & Winkler, Thorsten, 2013. "Bootstrap based model checks with missing binary response data," Statistics & Probability Letters, Elsevier, vol. 83(1), pages 219-226.
    2. Srihera, Ramidha & Stute, Winfried, 2010. "Nonparametric comparison of regression functions," Journal of Multivariate Analysis, Elsevier, vol. 101(9), pages 2039-2059, October.

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    Keywords

    Marked empirical process;

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