Sharp bounds on the relative treatment effect for ordinal outcomes

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)

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Published in:Biometrics 2020-06, Vol.76 (2), p.664-669
Main Authors: Lu, Jiannan, Zhang, Yunshu, Ding, Peng
Format: Article
Language:English
Subjects:
causal inference
Parameter identification
partial identification
potential outcomes
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description 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)
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subjects causal inference
Parameter identification
partial identification
potential outcomes
title Sharp bounds on the relative treatment effect for ordinal outcomes
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