Department of Psychology.
Psychol Assess. 2013 Sep;25(3):769-79. doi: 10.1037/a0032541. Epub 2013 May 6.
Computerized adaptive testing (CAT) is an emerging technology in the personality assessment literature given the greater efficiency it affords compared with traditional methods. However, few studies have directly compared the efficiency and validity of 2 competing methods for personality CAT: (a) methods based on item response theory (IRT-CAT) versus (b) methods based on the countdown method (CM-CAT). To that end, we conducted real-data simulations with previously collected responses (N = 8,690) to the Schedule for Nonadaptive and Adaptive Personality (SNAP). Three CAT algorithms (IRT-CAT, IRT-CAT with 5-item minimum, CM-CAT) were evaluated for item savings, classification accuracy, and convergent/discriminant validity. All CATs yielded lower classification accuracy and validity than traditional testing but required 18%-86% fewer items. Ultimately, the IRT-CAT, with minimum 5-item requirement, struck the most ideal balance of highest item savings, and generally fewer costs to validity and accuracy. These results confirm findings regarding item savings trends from previous CAT studies. In addition, this study provides a model for how the validity and precision of CATs may be compared across personality assessments.
计算机化自适应测验(CAT)是人格评估文献中一种新兴的技术,因为它比传统方法更有效率。然而,很少有研究直接比较人格 CAT 的两种竞争方法的效率和有效性:(a)基于项目反应理论的方法(IRT-CAT)与(b)基于倒计时方法的方法(CM-CAT)。为此,我们使用先前收集到的对非适应和适应人格量表(SNAP)的反应(N=8690)进行了真实数据模拟。评估了三种 CAT 算法(IRT-CAT、最小 5 项 IRT-CAT、CM-CAT)的项目节省、分类准确性和收敛/区分效度。所有 CAT 的分类准确性和有效性都低于传统测试,但需要的项目数减少了 18%-86%。最终,具有最小 5 项要求的 IRT-CAT 达到了最高项目节省和通常较少的有效性和准确性成本之间的最理想平衡。这些结果证实了先前 CAT 研究中关于项目节省趋势的发现。此外,本研究提供了一种模型,可以比较人格评估中 CAT 的有效性和精度。