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Simple conservative confidence intervals for comparing matched proportions

  • Jonsson, Robert

    ()

    (Department of Economics)

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    Unconditional confidence intervals (CIs) for the difference between marginal proportions in matched pairs data have essentially been based on improvements of Wald’s large-sample statistic. The latter are approximate and non-conservative. In some situations it may be of importance that CIs are conservative, e.g. when claiming bio-equivalence in small samples. Existing methods for constructing conservative CIs are computer intensive and are not suitable for sample size determination in planned stu... moredies. This paper presents a new simple method by which conservative CIs are readily computed. The method gives CIs that are comparable with earlier conservative methods concerning coverage probabilities and lengths. However, the new method can only be used if the proportions in the discordant cells p and q satisfies , but this is luckily the case in most applications and several examples are given. The new method is compared with previously suggested approximate and exact methods in large-scale simulations.

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    File URL: http://gupea.ub.gu.se/handle/2077/24353
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    Paper provided by Statistical Research Unit, Department of Economics, School of Business, Economics and Law, University of Gothenburg in its series Research Reports with number 2011:1.

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    Length: 22 pages
    Date of creation: 04 Feb 2011
    Date of revision:
    Handle: RePEc:hhs:gunsru:2011_001
    Contact details of provider: Postal:
    Statistical Research Unit, University of Gothenburg, Box 640, SE 40530 GÖTEBORG

    Web page: http://www.statistics.gu.se/

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    1. Huey-Miin Hsueh & Jen-Pei Liu & James J. Chen, 2001. "Unconditional Exact Tests for Equivalence or Noninferiority for Paired Binary Endpoints," Biometrics, The International Biometric Society, vol. 57(2), pages 478-483, 06.
    2. Marianne Frisen & Eva Andersson & Linus Schioler, 2010. "Evaluation of multivariate surveillance," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(12), pages 2089-2100.
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