Wolfe Christopher R, Fisher Christopher R
Miami University Oxford, Ohio, USA.
Learn Individ Differ. 2013 Jun 1;25:1-11. doi: 10.1016/j.lindif.2013.03.003.
Little is known about individual differences in integrating numeric base-rates and qualitative text in making probability judgments. Fuzzy-Trace Theory predicts a preference for fuzzy processing. We conducted six studies to develop the FPPI, a reliable and valid instrument assessing individual differences in this fuzzy processing preference. It consists of 19 probability estimation items plus 4 "M-Scale" items that distinguish simple pattern matching from "base rate respect." Cronbach's Alpha was consistently above 0.90. Validity is suggested by significant correlations between FPPI scores and three other measurers: "Rule Based" Process Dissociation Procedure scores; the number of conjunction fallacies in joint probability estimation; and logic index scores on syllogistic reasoning. Replicating norms collected in a university study with a web-based study produced negligible differences in FPPI scores, indicating robustness. The predicted relationships between individual differences in base rate respect and both conjunction fallacies and syllogistic reasoning were partially replicated in two web-based studies.
关于在进行概率判断时整合数字基础比率和定性文本方面的个体差异，我们所知甚少。模糊痕迹理论预测了对模糊处理的偏好。我们进行了六项研究来开发FPPI，这是一种评估这种模糊处理偏好方面个体差异的可靠且有效的工具。它由19个概率估计项目加4个“M量表”项目组成，这些项目区分了简单模式匹配和“尊重基础比率”。克朗巴哈系数始终高于0.90。FPPI分数与其他三种测量方法之间的显著相关性表明了其有效性：“基于规则”的过程分离程序分数；联合概率估计中的合取谬误数量；以及三段论推理的逻辑指数分数。在一项大学研究中收集的规范与一项基于网络的研究中重复收集，FPPI分数的差异可忽略不计，表明其稳健性。在两项基于网络的研究中，部分重复了基础比率尊重方面的个体差异与合取谬误和三段论推理之间的预测关系。
