A New Method for Scoring Additive Multi- attributeValue Models Using Pairwise Rankings of Alternatives
A New Method for Scoring Additive Multi- attributeValue Models Using Pairwise Rankings of Alternatives
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DOI：
10.1002/mcda.428
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发表时间：
2008-05-01
影响因子：
2
通讯作者：
Ombler, Franz
中科院分区：
文献类型：
--
作者：
Hansen, Paul;Ombler, Franz
提出了一种确定具有性能类别的可加多属性值模型点值的新方法。该方法，我们称之为PAPRIKA（所有可能的备选方案的潜在所有成对排序），涉及决策者成对排序潜在的所有非支配对的所有可能的备选方案表示的价值模型。通过将所有隐式排名的对识别为显式排名的对的推论的方法，将显式排名的对的数量最小化。我们报告模拟的方法的使用，并表明，如果决策者明确排名对定义的两个标准在同一时间，由价值模型产生的替代品的整体排名是非常高度相关的真实排名。因此，在大多数实际情况下，决策者不太可能需要对两个以上标准定义的配对进行排序，从而减少了启发负担。我们还描述了一个成功的现实世界的应用程序，涉及评分的价值模型，优先考虑在新西兰的心脏手术患者。我们的结论是，虽然新的方法需要更多的判断比传统的评分方法，判断的类型（成对排名的非支配对）可以说是更简单，并可能合理地预期，以反映决策者的偏好更准确。版权所有（C）2009约翰威利父子有限公司
We present a new method for determining the point values for additive multi-attribute value models with performance categories. The method, which we refer to as PAPRIKA (Potentially All Pairwise RanKings of all possible Alternatives), involves the decision-maker pairwise ranking potentially all undominated pairs of all possible alternatives represented by the value model. The number of pairs to be explicitly ranked is minimized by the method identifying all pairs implicitly ranked as corollaries of the explicitly ranked pairs. We report on simulations of the method's use and show that if the decision-maker explicitly ranks pairs defined on just two criteria at-a-time, the overall ranking of alternatives produced by the value model is very highly correlated with the true ranking. Therefore, for most practical purposes decision-makers are unlikely to need to rank pairs defined on more than two criteria, thereby reducing the elicitation burden. We also describe a successful real-world application involving the scoring of a value model for prioritizing patients for cardiac surgery in New Zealand. We conclude that although the new method entails more judgments than traditional scoring methods, the type of judgment (pairwise rankings of undominated pairs) is arguably simpler and might reasonably be expected to reflect the preferences of decision-makers more accurately. Copyright (C) 2009 John Wiley & Sons, Ltd.