Confidence intervals for a difference between proportions based on paired data

Man Lai TANG*, Man Ho Ling, Leevan LING, Guoliang Tian

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Pages (from-to)86-96
Number of pages11
JournalStatistics in Medicine
Volume29
Issue number1
DOIs
Publication statusPublished - 15 Jan 2010

Scopus Subject Areas

  • Epidemiology
  • Statistics and Probability

User-Defined Keywords

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

Fingerprint

Dive into the research topics of 'Confidence intervals for a difference between proportions based on paired data'. Together they form a unique fingerprint.

Cite this