USBE, Department of Statistics, Umeå University, 90187 , Umeå, Sweden.
Department of Psychology, McGill University, Montreal, Canada.
Psychometrika. 2019 Mar;84(1):310-322. doi: 10.1007/s11336-018-9639-4. Epub 2018 Oct 22.
The aim of this paper is to discuss nonparametric item response theory scores in terms of optimal scores as an alternative to parametric item response theory scores and sum scores. Optimal scores take advantage of the interaction between performance and item impact that is evident in most testing data. The theoretical arguments in favor of optimal scoring are supplemented with the results from simulation experiments, and the analysis of test data suggests that sum-scored tests would need to be longer than an optimally scored test in order to attain the same level of accuracy. Because optimal scoring is built on a nonparametric procedure, it also offers a flexible alternative for estimating item characteristic curves that can fit items that do not show good fit to item response theory models.
本文旨在讨论非参数项目反应理论分数，将其作为参数项目反应理论分数和总分的替代方法，以最优分数的形式呈现。最优分数利用了大多数测试数据中表现和项目影响之间的相互作用。支持最优评分的理论依据得到了模拟实验结果的补充，对测试数据的分析表明，为了达到相同的准确性，总分测试需要比最优评分测试更长。由于最优评分是基于非参数程序构建的，它还为估计项目特征曲线提供了一种灵活的替代方法，这些曲线可以拟合不符合项目反应理论模型的项目。
