University of Hamburg, Von-Melle-Park 5, 20146, Hamburg, Germany.
Psychometrika. 2018 Sep;83(3):563-585. doi: 10.1007/s11336-018-9613-1. Epub 2018 Apr 12.
Since Hooker, Finkelman and Schwartzman (Psychometrika 74(3): 419-442, 2009) it is known that person parameter estimates from multidimensional latent variable models can induce unfair classifications via paradoxical scoring effects. The open question as to whether there is a fair and at the same time multidimensional scoring scheme with adequate statistical properties is addressed in this paper. We develop a theorem on the existence of a fair, multidimensional classification scheme in the context of the classical linear factor analysis model and show how the computation of the scoring scheme can be embedded in the context of linear programming. The procedure is illustrated in the framework of scoring the Wechsler Adult Intelligence Scale (WAIS-IV).
自胡克、芬克尔曼和施瓦茨曼（Psychometrika 74(3): 419-442, 2009）以来，人们已经知道多维潜在变量模型中的个体参数估计可能会通过矛盾评分效应导致不公平的分类。本文旨在探讨是否存在一种公平且同时具有充分统计性质的多维评分方案。我们在经典线性因子分析模型的背景下提出了一个关于公平多维分类方案存在性的定理，并展示了如何将评分方案的计算嵌入线性规划的背景中。该过程在威克斯勒成人智力量表（WAIS-IV）的评分框架中进行了说明。
