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WIN INDICES AND RISK INDICES FOR BINARY OUTCOMES

  • Changyong Feng
  • , Hongyue Wang
  • , Tong Wu
  • Departments of Biostatistics and Computational Biology
  • University of Rochester

Research output: Contribution to journal › Article › peer-review

Abstract

The win ratio has become a popular method for analyzing data with prioritized composite outcomes. In this paper, we apply the win ratio method to the study of binary outcomes, derive the analytical relationships between risk indices and win indices, and provide new interpretations of standard risk indices from the perspective of win indices. Furthermore, we prove that, among a large family of win indices, the win odds is the unique metric that is equivalent to the win difference (risk difference).

Original languageEnglish
Pages (from-to)1-8
Number of pages8
JournalJournal of Applied Probability and Statistics
Volume21
Issue number2
StatePublished - Aug 2026

ASJC Scopus Subject Areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty
  • Applied Mathematics

Keywords

  • Risk difference
  • Risk ratio
  • Win difference
  • Win odds
  • Win Ratio

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