Goldhammer Frank, Steinwascher Merle A, Kroehne Ulf, Naumann Johannes
German Institute for International Educational Research (DIPF), Frankfurt am Main, Germany.
Centre for International Student Assessment (ZIB) e.V., Frankfurt am Main, Germany.
Br J Math Stat Psychol. 2017 May;70(2):238-256. doi: 10.1111/bmsp.12099.
Completing test items under multiple speed conditions avoids the performance measure being confounded with individual differences in the speed-accuracy compromise, and offers insights into the response process, that is, how response time relates to the probability of a correct response. This relation is traditionally represented by two conceptually different functions: the speed-accuracy trade-off function (SATF) across conditions relating the condition average response time to the condition average of accuracy, and the conditional accuracy function (CAF) within a condition describing accuracy conditional on response time. Using a generalized linear mixed modelling approach, we propose an item response modelling framework that is suitable for item response and response time data from experimental speed conditions. The proposed SATF and CAF model accommodates response time effects between conditions (i.e., person and item SATF slope) and within conditions (i.e., residual CAF slopes), captures person and item differences in these effects, and is suitable for measures with a strong speed component. Moreover, for a single condition a CAF model is proposed distinguishing person, item and residual CAF. The properties of the models are illustrated with an empirical example.
在多种速度条件下完成测试项目可避免将性能测量与速度 - 准确性权衡中的个体差异相混淆，并能深入了解反应过程，即反应时间与正确反应概率之间的关系。这种关系传统上由两个概念上不同的函数表示：跨条件的速度 - 准确性权衡函数（SATF），它将条件平均反应时间与条件平均准确性相关联；以及条件内的条件准确性函数（CAF），它描述了基于反应时间的准确性。使用广义线性混合建模方法，我们提出了一个项目反应建模框架，该框架适用于来自实验速度条件的项目反应和反应时间数据。所提出的SATF和CAF模型考虑了条件之间（即人和项目SATF斜率）以及条件内（即残差CAF斜率）的反应时间效应，捕捉了这些效应中的人和项目差异，并且适用于具有强速度成分的测量。此外，针对单个条件，提出了一个区分人和项目以及残差CAF的CAF模型。通过一个实证例子说明了模型的特性。
