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Accurate interval estimation for the risk difference in an incomplete correlated 2 × 2 table: Calf immunity analysis

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  • Hezhi Lu
  • Fengjing Cai
  • Yuan Li
  • Xionghui Ou

Abstract

Interval estimation with accurate coverage for risk difference (RD) in a correlated 2 × 2 table with structural zero is a fundamental and important problem in biostatistics. The score test-based and Bayesian tail-based confidence intervals (CIs) have good coverage performance among the existing methods. However, as approximation approaches, they have coverage probabilities lower than the nominal confidence level for finite and moderate sample sizes. In this paper, we propose three new CIs for RD based on the fiducial, inferential model (IM) and modified IM (MIM) methods. The IM interval is proven to be valid. Moreover, simulation studies show that the CIs of fiducial and MIM methods can guarantee the preset coverage rate even for small sample sizes. More importantly, in terms of coverage probability and expected length, the MIM interval outperforms other intervals. Finally, a real example illustrates the application of the proposed methods.

Suggested Citation

  • Hezhi Lu & Fengjing Cai & Yuan Li & Xionghui Ou, 2022. "Accurate interval estimation for the risk difference in an incomplete correlated 2 × 2 table: Calf immunity analysis," PLOS ONE, Public Library of Science, vol. 17(7), pages 1-23, July.
  • Handle: RePEc:plo:pone00:0272007
    DOI: 10.1371/journal.pone.0272007
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    References listed on IDEAS

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