Cheng P W, Novick L R
Department of Psychology, University of California, Los Angeles 90024-1563.
Psychol Rev. 1992 Apr;99(2):365-82. doi: 10.1037/0033-295x.99.2.365.
The covariation component of everyday causal inference has been depicted, in both cognitive and social psychology as well as in philosophy, as heterogeneous and prone to biases. The models and biases discussed in these domains are analyzed with respect to focal sets: contextually determined sets of events over which covariation is computed. Moreover, these models are compared to our probabilistic contrast model, which specifies causes as first and higher order contrasts computed over events in a focal set. Contrary to the previous depiction of covariation computation, the present assessment indicates that a single normative mechanism--the computation of probabilistic contrasts--underlies this essential component of natural causal induction both in everyday and in scientific situations.
在认知心理学、社会心理学以及哲学领域，日常因果推理的共变成分都被描述为具有异质性且容易产生偏差。这些领域中所讨论的模型和偏差是根据焦点集进行分析的：焦点集是由上下文确定的事件集，在这些事件集上计算共变。此外，还将这些模型与我们的概率对比模型进行了比较，该模型将原因指定为在焦点集中的事件上计算的一阶和高阶对比。与之前对共变计算的描述相反，目前的评估表明，一个单一的规范机制——概率对比的计算——是日常和科学情境中自然因果归纳这一重要组成部分的基础。
