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有序效应量度量的建模与推断

Modeling and inference for an ordinal effect size measure.

作者信息

Ryu Euijung, Agresti Alan

机构信息

Department of Health Sciences Research, Mayo Clinic, Rochester, MN 55905, U.S.A.

出版信息

Stat Med. 2008 May 10;27(10):1703-17. doi: 10.1002/sim.3079.

Abstract

An ordinal measure of effect size is a simple and useful way to describe the difference between two ordered categorical distributions. This measure summarizes the probability that an outcome from one distribution falls above an outcome from the other, adjusted for ties. We develop and compare confidence interval methods for the measure. Simulation studies show that with independent multinomial samples, confidence intervals based on inverting the score test and a pseudo-score-type test perform well. This score method also seems to work well with fully-ranked data, but for dependent samples a simple Wald interval on the logit scale can be better with small samples. We also explore how the ordinal effect size measure relates to an effect measure commonly used for normal distributions, and we consider a logit model for describing how it depends on explanatory variables. The methods are illustrated for a study comparing treatments for shoulder-tip pain.

摘要

效应大小的序数测量是描述两个有序分类分布之间差异的一种简单而有用的方法。该测量总结了一个分布的结果高于另一个分布的结果的概率,并对平局情况进行了调整。我们开发并比较了该测量的置信区间方法。模拟研究表明,对于独立的多项样本,基于对分数检验和伪分数型检验进行反演得到的置信区间表现良好。这种分数方法对于完全排序的数据似乎也很有效,但对于相关样本,在小样本情况下,对数尺度上的简单Wald区间可能更好。我们还探讨了序数效应大小测量与常用于正态分布的效应测量之间的关系,并考虑了一个对数模型来描述它如何依赖于解释变量。通过一项比较肩尖疼痛治疗方法的研究对这些方法进行了说明。

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