Ashby F G, Lee W W
Department of Psychology, University of California, Santa Barbara 93106.
J Exp Psychol Gen. 1991 Jun;120(2):150-72. doi: 10.1037//0096-3445.120.2.150.
In this article, the relation between the identification, similarity judgment, and categorization of multidimensional perceptual stimuli is studied. The theoretical analysis focused on general recognition theory (GRT), which is a multidimensional generalization of signal detection theory. In one application, 2 Ss first identified a set of confusable stimuli and then made judgments of their pairwise similarity. The second application was to Nosofsky's (1985b, 1986) identification-categorization experiment. In both applications, a GRT model accounted for the identification data better than Luce's (1963) biased-choice model. The identification results were then used to predict performance in the similarity judgment and categorization conditions. The GRT identification model accurately predicted the similarity judgments under the assumption that Ss allocated attention to the 2 stimulus dimensions differently in the 2 tasks. The categorization data were predicted successfully without appealing to the notion of selective attention. Instead, a simpler GRT model that emphasized the different decision rules used in identification and categorization was adequate.
本文研究了多维感知刺激的识别、相似性判断和分类之间的关系。理论分析聚焦于通用识别理论（GRT），它是信号检测理论的多维推广。在一项应用中，两名被试首先识别一组易混淆的刺激，然后对它们的两两相似性进行判断。第二项应用是针对诺索夫斯基（1985b，1986）的识别-分类实验。在这两项应用中，一个GRT模型比卢斯（1963）的偏向选择模型能更好地解释识别数据。然后，利用识别结果预测相似性判断和分类条件下的表现。GRT识别模型在假设被试在两项任务中对两个刺激维度分配注意力不同的情况下，准确地预测了相似性判断。在不涉及选择性注意概念的情况下，成功地预测了分类数据。相反，一个更简单的GRT模型，强调在识别和分类中使用的不同决策规则，就足够了。
