The Bradley-Terry model is widely used for pairwise comparison data analysis. In this paper, we analyze the asymptotic behavior of the maximum likelihood estimator of the Bradley-Terry model in its logistic parameterization, under a general class of linear identifiability constraints. We show that the constraint requiring the Bradley-Terry scores for all compared objects to sum to zero minimizes the sum of the variances of the estimated scores, and recommend using this constraint in practice.

翻译：Bradley-Terriy模型被广泛用于对比比较数据分析。在本文中,我们分析了布拉德利-Terriy模型最大可能性估测者在其后勤参数化中,在一般线性可辨度限制类别下无症状行为。我们表明,要求所有比较对象的Bradley-Terriy分数以总和为零的制约将估计分数差异的总和降至零,并建议在实践中使用这一限制。