Center for Doctoral Studies in Social and Behavioral Sciences, University of Mannheim.
Psychology III, University of Mannheim.
J Exp Psychol Learn Mem Cogn. 2010 Jan;36(1):123-134. doi: 10.1037/a0017518.
The fast-and-frugal recognition heuristic (RH) theory provides a precise process description of comparative judgments. It claims that, in suitable domains, judgments between pairs of objects are based on recognition alone, whereas further knowledge is ignored. However, due to the confound between recognition and further knowledge, previous research lacked an unbiased measure of RH use. Also, model comparisons have not been based on goodness-of-fit and model complexity as criteria. To overcome both limitations we introduce and test a multinomial processing tree model showing that it fits empirical data and provides an unbiased measure of RH use. Analyses of 8 data sets reveal that the RH alone cannot account for the data, not even when it is implemented in a probabilistic way. That is, information integration beyond recognition plays a vital role and cannot merely account for empirical data better due to model flexibility. Also, we present several validations of the central model parameter and provide demonstrations of how the model can be applied to study the less-is-more effect as well as determinants of (and individual differences in) RH use. (PsycINFO Database Record (c) 2009 APA, all rights reserved).
快速而简约的识别启发式（RH）理论为比较判断提供了一个精确的过程描述。它声称，在合适的领域，对两个对象的判断仅基于识别，而忽略了其他知识。然而，由于识别和进一步的知识之间存在混淆，之前的研究缺乏对 RH 使用的无偏测量。此外，模型比较也没有基于拟合优度和模型复杂性作为标准。为了克服这两个局限性，我们引入并测试了一个多项处理树模型，表明它可以拟合经验数据，并提供了对 RH 使用的无偏测量。对 8 个数据集的分析表明，即使 RH 以概率的方式实施，它也不能解释数据，甚至不能单独解释数据。也就是说，超越识别的信息整合起着至关重要的作用，并且不能仅仅因为模型的灵活性而更好地解释经验数据。此外，我们还对中心模型参数进行了多次验证，并演示了如何应用该模型来研究少即是多的效应，以及 RH 使用的决定因素（和个体差异）。（PsycINFO 数据库记录（c）2009 APA，保留所有权利）。
