Confidence intervals for a difference between proportions based on paired data

Man Lai TANG, Man Ho Alpha LING, Leevan LING, Guoliang TIAN

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19 Citations (Scopus)

Abstract

We construct several explicit asymptotic two-sided confidence intervals (CIs) for the difference between two correlated proportions using the method of variance of estimates recovery (MOVER). The basic idea is to recover variance estimates required for the proportion difference from the confidence limits for single proportions. The CI estimators for a single proportion, which are incorporated with the MOVER, include the Agresti-Coull, the Wilson, and the Jeffreys CIs. Our simulation results show that the MOVER-type CIs based on the continuity corrected U coefficient and the Tango score CI perform satisfactory in small sample designs and spare data structures. We illustrate the proposed CIs with several real examples. Copyright © 2009 John Wiley & Sons, Ltd.
Original languageEnglish
Pages (from-to)86-96
JournalStatistics in Medicine
Volume29
Issue number1
DOIs
Publication statusPublished - 2010

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Paired Data
Confidence interval
Proportion
Recovery
Estimate
Confidence Limits
Small Sample
Data Structures
Estimator
Coefficient

Citation

Tang, M-L., Ling, M-H., Ling, L., Tian, G. (2010). Confidence intervals for a difference between proportions based on paired data. Statistics in Medicine, 29(1), 86-96.

Keywords

  • Agresti-coull interval
  • Jeffreys interval
  • Method of variance estimates recovery
  • Paired binary data
  • Tango score interval
  • Wilson score interval