School of Social Sciences, University of Dundee, UK.
Warwick Business School, University of Warwick, UK.
Cognition. 2020 May;198:104203. doi: 10.1016/j.cognition.2020.104203. Epub 2020 Jan 31.
While parameters are crucial components of cognitive models, relatively little importance has been given to their units. We show that this has lead to some parameters to be contaminated, introducing an artifactual correlation between them. We also show that this has led to the illegal comparison of parameters with different units of measurement - this may invalidate parameter comparisons across participants, conditions, groups, or studies. We demonstrate that this problem affects two related models: Stevens' power law and Rachlin's delay discounting model. We show that it may even affect models which superficially avoid the incompatible units problem, such as hyperbolic discounting. We present simulation results to demonstrate the extent of the issues caused by the muddled units problem. We offer solutions in order to avoid the problem in the future or to aid in re-interpreting existing datasets.
虽然参数是认知模型的关键组成部分，但它们的单位相对较少受到重视。我们表明，这导致了一些参数受到污染，在它们之间引入了人为的相关性。我们还表明，这导致了具有不同度量单位的参数之间的非法比较 - 这可能会使参与者、条件、组或研究之间的参数比较无效。我们证明了这个问题影响了两个相关的模型：史蒂文斯幂律和雷奇林的延迟折扣模型。我们表明，它甚至可能影响到表面上避免不兼容单位问题的模型，例如双曲线折扣。我们提供模拟结果来说明单位混乱问题造成的问题的严重程度。我们提供了解决方案，以避免将来出现问题，或帮助重新解释现有数据集。
