标题： 配对比较数据的模型：侧重于相关数据的回顾 显示英文标题

标题： Models for Paired Comparison Data: A Review with Emphasis on Dependent Data

摘要： Thurstonian 模型和 Bradley-Terry 模型是配对比较数据分析中最常用的两种模型。自它们被提出以来，在不同领域提出了许多发展与改进。本文对这些扩展进行了更新概述，包括如何考虑对象特异性和主体特异性协变量，以及如何处理有序的配对比较数据。特别强调了依赖性比较模型。尽管这些模型更加现实，但由于数值上的困难，其应用变得复杂。因此，我们集中讨论实现问题。具体而言，探索了依赖性配对比较数据模型的成对似然方法，并通过模拟研究比较了最大成对似然与其他有限信息估计方法的表现。本文使用学生进行的大学配对比较的真实数据集来说明该方法论。 显示英文摘要

摘要： Thurstonian and Bradley-Terry models are the most commonly applied models in the analysis of paired comparison data. Since their introduction, numerous developments have been proposed in different areas. This paper provides an updated overview of these extensions, including how to account for object- and subject-specific covariates and how to deal with ordinal paired comparison data. Special emphasis is given to models for dependent comparisons. Although these models are more realistic, their use is complicated by numerical difficulties. We therefore concentrate on implementation issues. In particular, a pairwise likelihood approach is explored for models for dependent paired comparison data, and a simulation study is carried out to compare the performance of maximum pairwise likelihood with other limited information estimation methods. The methodology is illustrated throughout using a real data set about university paired comparisons performed by students.