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Estimating ordered binomial proportions with the use of group testing

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  • Joshua M. Tebbs

Abstract

This paper considers group testing when the probability of response is increasing across the levels of an observed covariate. We illustrate how previously known results in order-restricted inference can be extended to situations wherein data are collected according to a group-testing protocol, and we derive maximum likelihood estimators for proportions under the increasing order restriction and group-testing model. Finally, we show how the use of group testing can dramatically reduce the bias and mean squared error of isotonic regression estimators obtained from one-at-a-time testing. These proposed methods are illustrated using data from an observational HIV study conducted in Houston, Texas. Copyright Biometrika Trust 2003, Oxford University Press.

Suggested Citation

  • Joshua M. Tebbs, 2003. "Estimating ordered binomial proportions with the use of group testing," Biometrika, Biometrika Trust, vol. 90(2), pages 471-477, June.
  • Handle: RePEc:oup:biomet:v:90:y:2003:i:2:p:471-477
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    Cited by:

    1. Juan Ding & Wenjun Xiong, 2015. "Robust group testing for multiple traits with misclassification," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(10), pages 2115-2125, October.
    2. Nguyen, Ngoc T. & Bish, Ebru K. & Bish, Douglas R., 2021. "Optimal pooled testing design for prevalence estimation under resource constraints," Omega, Elsevier, vol. 105(C).
    3. Graham Hepworth & Ray Watson, 2009. "Debiased estimation of proportions in group testing," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 58(1), pages 105-121, February.
    4. Jie Mi, 2019. "Some limit results in estimation of proportion based on group testing," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 82(8), pages 1021-1038, November.

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