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Sharp bounds on the relative treatment effect for ordinal outcomes

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  • Jiannan Lu
  • Yunshu Zhang
  • Peng Ding

Abstract

For ordinal outcomes, the average treatment effect is often ill‐defined and hard to interpret. Echoing Agresti and Kateri, we argue that the relative treatment effect can be a useful measure, especially for ordinal outcomes, which is defined as γ=pr{Yi(1)>Yi(0)}−pr{Yi(1)

Suggested Citation

  • Jiannan Lu & Yunshu Zhang & Peng Ding, 2020. "Sharp bounds on the relative treatment effect for ordinal outcomes," Biometrics, The International Biometric Society, vol. 76(2), pages 664-669, June.
    • Handle: RePEc:bla:biomet:v:76:y:2020:i:2:p:664-669
    DOI: 10.1111/biom.13148
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    References listed on IDEAS

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    Cited by:

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    2. Di Francesco, Riccardo & Mellace, Giovanni, 2025. "Causal inference for qualitative outcomes," Economics Letters, Elsevier, vol. 256(C).
    3. Ailei Ding & Hanmei Sun, 2025. "Bounds on Causal Effects Based on Expectations in Ordered-Outcome Models," Mathematics, MDPI, vol. 13(19), pages 1-15, September.

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