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Moderated paired comparisons: a generalized Bradley-Terry model for continuous data using a discontinuous penalized likelihood function

机译:适度的成对比较:使用不连续惩罚似然函数的连续数据的广义Bradley-Terry模型

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摘要

Standard paired comparison models are widely used in circumstances where a measure of preference is available on a sequence or collection of pairwise comparisons between a group of objects or treatments. Typically, the measure of preference observations takes the form of simple binary outcomes, indicating which of the two objects or treatments in a particular comparison is preferred. Common examples of such situations include models of choice behaviour in politics or marketing, comparisons of medical treatments or in the realm of sports rankings. We investigate situations where the observed measure of preference for the paired comparisons is instead a continuous outcome indicating not simply the direction of preference but the degree of preference as well; in particular, we present, as a motivating example, a ranking analysis of the top 12 international limited overs cricket teams, with an appropriately defined margin of victory in individual matches playing the role of the measure of preference. We propose a new method, which is termed moderated paired comparisons, that is based on fitting a penalized likelihood model to the observed margins of victory. Importantly, the structure of the penalty function chosen allows for the model to assign differential importance to the information that is contained solely in the dichotomous win-loss outcome of a match as against that contained in the actual margin of the victory.
机译:标准配对比较模型广泛用于在一组对象或处理之间的序列比较或成对比较集合中可以使用偏好度量的情况。通常,偏好观察的度量采用简单的二进制结果的形式,指示在特定比较中这两个对象或处理中的哪一个是优选的。这种情况的常见示例包括政治或市场营销中的选择行为模型,医疗比较或体育排名领域。我们调查了这样的情况,即观察到的配对比较的偏好度量是连续的结果,不仅表明偏好的方向,还表明偏好的程度。特别是,作为激励性的例子,我们提供了对排名前12位的国际受限板球球队的排名分析,其中适当定义的个人比赛获胜率将发挥偏爱的作用。我们提出了一种新的方法,称为“适度配对比较”,该方法基于将惩罚似然模型拟合到观察到的获胜幅度。重要的是,所选择的罚分函数的结构允许模型为仅包含在比赛的二分胜负结果中的信息(相对于实际胜率中所包含的信息)分配不同的重要性。

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