Kvam Peter D, Pleskac Timothy J
Michigan State University, United States; Max Planck Institute for Human Development, Germany.
Max Planck Institute for Human Development, Germany.
Cognition. 2016 Jul;152:170-180. doi: 10.1016/j.cognition.2016.04.008. Epub 2016 Apr 16.
Evidence for different hypotheses is often treated as a singular construct, but it can be dissociated into two parts: its strength, the proportion of pieces of information favoring one hypothesis; and its weight, the total number of pieces of information available. However, cognitive and neural models of evidence accumulation often make a proportional representation assumption, implying that people take these two factors into account equally when making their decisions and judgments. We examine this assumption by directly manipulating the number of samples and the proportion favoring either of two alternatives in dynamic decision making and judgment tasks. The results suggest that people tend to over-emphasize the strength of evidence relative to its weight in both an optional-stopping decision task and a probability judgment task. In a drift-diffusion model, this is reflected by drift rates that are determined foremost by strength with a smaller influence of weight. This result challenges the proportional representation assumption made by existing models of judgment and decision-making, and calls into question modeling evidence accumulation as a Bayesian belief updating process.
支持不同假设的证据通常被视为一个单一的结构，但它可以分解为两个部分：其强度，即支持一个假设的信息片段的比例；及其权重，即可用信息片段的总数。然而，证据积累的认知和神经模型通常做出比例表征假设，这意味着人们在做出决策和判断时会平等地考虑这两个因素。我们通过在动态决策和判断任务中直接操纵样本数量以及支持两种选择中任一种的比例来检验这一假设。结果表明，在可选停止决策任务和概率判断任务中，人们相对于证据权重往往过度强调证据强度。在漂移扩散模型中，这表现为漂移率主要由强度决定，权重的影响较小。这一结果挑战了现有判断和决策模型所做的比例表征假设，并对将证据积累建模为贝叶斯信念更新过程提出了质疑。
