Sheu Ching-Fan, Lee Yuh-Shiow, Shih Pei-Ying
Department of Psychology, National Chung Cheng University, Chia-Yi, Taiwan.
Behav Res Methods. 2008 Aug;40(3):722-7. doi: 10.3758/brm.40.3.722.
Experiments in which recognition performance is measured sometimes involve only a small number of observations per subject, rendering d' analysis unreliable (Schooler & Shiffrin, 2005). Here, we introduce, in signal detection models, subject-specific random variables to account for heterogeneous hit and false alarm rates among individuals. Population d' effects for comparing groups are estimated, in this approach, by pooling information from a sample of subjects across experimental conditions. The method is validated by a simulation study and is illustrated with an analysis of the effect of neutral and emotional words on recognition performance, employing the emotional Stroop task (Lee & Shih, 2007).
有时，测量识别性能的实验每个受试者仅涉及少量观察结果，这使得d'分析不可靠（Schooler & Shiffrin，2005）。在此，我们在信号检测模型中引入特定于受试者的随机变量，以解释个体之间不同的击中率和误报率。在这种方法中，通过汇总来自跨实验条件的受试者样本的信息来估计用于比较组的总体d'效应。该方法通过模拟研究得到验证，并通过对中性词和情感词对识别性能的影响进行分析来说明，采用情感斯特鲁普任务（Lee & Shih，2007）。
