Scoring from Contests.
Scoring from Contests.
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DOI：
10.1093/pan/mpt018
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发表时间：
2014-01
期刊：
影响因子：
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通讯作者：
Penn EM
中科院分区：
文献类型：
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作者：
Schnakenberg KE;Penn EM
本文提出了一种根据“竞赛”结果对备选方案进行评分的新模型。该模型是配对比较方法的概括，以适应任意大小的替代方案集之间的比较，其中结果是固定奖励的任何划分。我们的方法也适用于不同数量的替代品之间的竞争。我们证明，在替代方案可比性的合理条件下，存在一个独特的分数集合，可以对每个替代方案的整体性能进行准确的估计，并满足有关选择概率的众所周知的公理。我们将该方法应用于几个问题，其中不同的选择集和连续结果可能会给标准评分方法带来问题。这些问题包括衡量网络数据的中心性以及通过“感觉温度计”对政治候选人进行评分。在后一种情况下，我们还使用该方法来发现并解决重新调整温度计数据的常见方法的潜在困难，以解决人际可比性问题。
This article presents a new model for scoring alternatives from “contest” outcomes. The model is a generalization of the method of paired comparison to accommodate comparisons between arbitrarily sized sets of alternatives in which outcomes are any division of a fixed prize. Our approach is also applicable to contests between varying quantities of alternatives. We prove that under a reasonable condition on the comparability of alternatives, there exists a unique collection of scores that produces accurate estimates of the overall performance of each alternative and satisfies a well-known axiom regarding choice probabilities. We apply the method to several problems in which varying choice sets and continuous outcomes may create problems for standard scoring methods. These problems include measuring centrality in network data and the scoring of political candidates via a “feeling thermometer.” In the latter case, we also use the method to uncover and solve a potential difficulty with common methods of rescaling thermometer data to account for issues of interpersonal comparability.