ArticleStatistica Sinica2026
WIN RATIO FOR PARTIALLY ORDERED DATA.
Article in Statistica Sinica, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
The win ratio, initially developed for time-to-event data, can be extended to any data type equipped with a partial order. We study this extension in both nonparametric inference and semiparametric regression. We begin by formulating the win ratio as an estimand of contrast between two populations with partially ordered responses, showing that it reduces to the familiar odds ratio in the case of binary data. For hypothesis testing, we prove that the empirical two-sample win ratio is consistent against stochastically ordered distributions and efficient against proportional odds alternatives under a total order. In regression, we model the conditional win ratio multiplicatively against covariates, extending logistic regression from binary to partially ordered responses. This model is implied by a generalized continuation-ratio logit model but requires fewer assumptions on the relationship between response levels. To make inference, we construct a class of weighted
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