Chapman G B
Department of Decision Sciences, University of Pennsylvania, Philadelphia 19104-6366.
J Exp Psychol Learn Mem Cogn. 1991 Sep;17(5):837-54. doi: 10.1037//0278-7393.17.5.837.
Recent research on contingency judgment indicates that the judged predictiveness of a cue is dependent on the predictive strengths of other cues. Two classes of models correctly predict such cue interaction: associative models and statistical models. However, these models differ in their predictions about the effect of trial order on cue interaction. In five experiments reported here, college students viewed trial-by-trial data regarding several medical symptoms and a disease, judging the predictive strength of each symptom with respect to the disease. The results indicate that trial order influences the manner in which cues interact, but that neither the associative nor the statistical models can fully account for the data pattern. A possible variation of an associative account is discussed.
近期关于偶然性判断的研究表明，线索的判断预测性取决于其他线索的预测强度。两类模型能够正确预测这种线索交互作用：联想模型和统计模型。然而，这些模型在关于试验顺序对线索交互作用的影响的预测上存在差异。在本文所报告的五项实验中，大学生查看了关于几种医学症状和一种疾病的逐次试验数据，判断每种症状相对于该疾病的预测强度。结果表明，试验顺序会影响线索交互的方式，但联想模型和统计模型都无法完全解释数据模式。本文讨论了联想模型的一种可能变体。
