Weese James D, Turner Ronna C, Ames Allison, Crawford Brandon, Liang Xinya
University of Arkansas, Fayetteville, AR, USA.
Indiana University Bloomington, Bloomington, IN, USA.
Educ Psychol Meas. 2022 Apr;82(2):307-329. doi: 10.1177/00131644211017267. Epub 2021 Jun 2.
A simulation study was conducted to investigate the heuristics of the SIBTEST procedure and how it compares with ETS classification guidelines used with the Mantel-Haenszel procedure. Prior heuristics have been used for nearly 25 years, but they are based on a simulation study that was restricted due to computer limitations and that modeled item parameters from estimates of ACT and ASVAB tests from 1987 and 1984, respectively. Further, suggested heuristics for data fitting a two-parameter logistic model (2PL) have essentially went unused since their original presentation. This simulation study incorporates a wide range of data conditions to recommend heuristics for both 2PL and three-parameter logistic (3PL) data that correspond with ETS's Mantel-Haenszel heuristics. Levels of agreement between the new SIBTEST heuristics and Mantel-Haenszel heuristics were similar for 2PL data and higher than prior SIBTEST heuristics for 3PL data. The new recommendations provide higher true-positive rates for 2PL data. Conversely, they displayed decreased true-positive rates for 3PL data. False-positive rates, overall, remained below the level of significance for the new heuristics. Unequal group sizes resulted in slightly larger false-positive rates than balanced designs for both prior and new SIBTEST heuristics, with rates less than alpha levels for equal ability distributions and unbalanced designs versus false-positive rates slightly higher than alpha with unequal ability distributions and unbalanced designs.
进行了一项模拟研究,以调查SIBTEST程序的启发式方法以及它与用于Mantel-Haenszel程序的ETS分类指南相比如何。先前的启发式方法已经使用了近25年,但它们基于一项由于计算机限制而受限的模拟研究,该研究分别根据1987年和1984年的ACT和ASVAB测试估计值对项目参数进行建模。此外,自最初提出以来,针对拟合双参数逻辑模型(2PL)数据的建议启发式方法基本上未被使用。这项模拟研究纳入了广泛的数据条件,以推荐与ETS的Mantel-Haenszel启发式方法相对应的2PL和三参数逻辑(3PL)数据的启发式方法。新的SIBTEST启发式方法与Mantel-Haenszel启发式方法之间的一致性水平在2PL数据中相似,在3PL数据中高于先前的SIBTEST启发式方法。新建议为2PL数据提供了更高的真阳性率。相反,它们在3PL数据中显示出真阳性率下降。总体而言,新启发式方法的假阳性率仍低于显著性水平。对于先前和新的SIBTEST启发式方法,不等的组大小导致的假阳性率略高于平衡设计,对于能力分布相等和不平衡设计,假阳性率低于α水平,而对于能力分布不相等和不平衡设计,假阳性率略高于α。