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Testing Under the Extended Koziol-Green Model

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Copula Theory and Its Applications

Part of the book series: Lecture Notes in Statistics ((LNSP,volume 198))

Abstract

In this chapter, we consider a non-parametric testing procedure for an extension of the Koziol-Green model under two types of informative censoring. For the first type of informative censoring, we allow the censoring time to depend on the lifetime through an Archimedean copula function. For the second type, we generalize the relationship between the marginal distributions of the censoring time and lifetime by means of another copula function on the observed time and censoring indicator. In addition, we describe a bootstrap procedure to approximate the null distribution of the test statistics and illustrate it on a practical data set on survival with malignant melanoma.

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Acknowledgements

The authors gratefully acknowledge the financial support from the IAP research Network P6/03 of the Belgian Government (Belgian Science Policy).

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Authors and Affiliations

  1. Interuniversity Institute for Biostatistics and Statistical Bioinformatics, Universiteit Hasselt, Diepenbeek, Belgium

    Auguste Gaddah & Roel Braekers

Authors
  1. Auguste Gaddah
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  2. Roel Braekers
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Corresponding author

Correspondence to Auguste Gaddah .

Editor information

Editors and Affiliations

  1. , Faculty of Mathematics Informatics, University of Warsaw, ul. Banacha 2, Warszawa, 02097, Poland

    Piotr Jaworski

  2. , Department of Knowledge-Based, Johannes Kepler Universität, Altenberger Straße 69, Linz, 4040, Austria

    Fabrizio Durante

  3. Ladislaus von Bortkiewicz Chair of Stati, C.A.S.E. Centre for Applied Statistics a, Humboldt-Universität zu Berlin, Unter den Linden 6, Berlin, 10099, Germany

    Wolfgang Karl Härdle

  4. , Mathematical Institute, Polish Academy of Sciences, ul. Chopina 12, Toruń, 87100, Poland

    Tomasz Rychlik

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Gaddah, A., Braekers, R. (2010). Testing Under the Extended Koziol-Green Model. In: Jaworski, P., Durante, F., Härdle, W., Rychlik, T. (eds) Copula Theory and Its Applications. Lecture Notes in Statistics(), vol 198. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12465-5_14

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