Confidence intervals for correlated proportion differences from paired data in a two-arm randomised clinical trial

Yanbo Pei, Man Lai TANG*, Weng Kee Wong, Jianhua Guo

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)

Abstract

Many key outcome measures for monitoring disease progression are based on summing across several paired domains. The scores from the paired domain in an individual are likely to be correlated and we present here an analysis of treatment effect at each domain that accounts for the correlation. We use the profile likelihood method, asymptotic score method, and three simple asymptotic methods and construct confidence intervals to compare proportions of responders in a two-arm randomised trial. We evaluate the performance of these confidence interval estimators with respect to their mean coverage probabilities, mean left-tail and right-tail non-coverage rates, and mean confidence widths. These methods are then applied to analyse a multi-centre randomised clinical trial for scleroderma patients.

Original languageEnglish
Pages (from-to)167-187
Number of pages21
JournalStatistical Methods in Medical Research
Volume21
Issue number2
DOIs
Publication statusPublished - Apr 2012

Scopus Subject Areas

  • Epidemiology
  • Statistics and Probability
  • Health Information Management

User-Defined Keywords

  • confidence interval estimation
  • correlated binary data
  • intraclass correlation
  • systemic sclerosis

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