Duplessis-Marcotte Félix, Caron Pier-Olivier, Marin Marie-France
Department of Psychology, Université du Québec À Montréal, Montreal, QC, H3C 3P8, Canada.
Stress, Trauma, Emotion, Anxiety, and Memory (STEAM) Lab, Research Center of the Institut Universitaire en Santé Mentale de Montréal, 7331 Hochelaga, Montreal, QC, H1N 3V2, Canada.
Cogn Affect Behav Neurosci. 2025 Mar 6. doi: 10.3758/s13415-025-01271-7.
The Somatic Marker Hypothesis, an influential neurobiological account of decision-making, states that emotional somatic markers (e.g., skin conductance responses) influence decision-making processes. Despite its prominence, the hypothesis remains controversial partly because of inconsistent results stemming from inappropriate statistical methods. Tasks designed to assess decision-making often use repeated measures designs, such as the Iowa Gambling Task (IGT), which requires participants to maximize profits by selecting 100 cards among four decks offering varying win-loss contingencies. Researchers often aggregate repeated measures into a single averaged value to simplify analyses, potentially committing an ecological fallacy by erroneously generalizing results obtained from aggregated data (i.e., interindividual effects) to individual repeated measurements (i.e., intraindividual effects). This paper addresses this issue by demonstrating how to analyze concurrent repeated measures of both independent and dependent variables using multilevel logistic models. First, the principles of logistic multilevel models are explained. Then, simulated and empirical IGT data are analyzed to compare the performance of traditional statistical approaches (i.e., general linear models) with multilevel logistic models. Our proposed multilevel logistic analyses address critical methodological gaps in decision-making research, ensuring more accurate interpretations of repeated measures data. This approach not only advances the study of the Somatic Marker Hypothesis but also provides a robust framework for similar research protocols, ultimately enhancing the reliability and validity of findings.
躯体标记假说，一种关于决策的有影响力的神经生物学解释，指出情绪躯体标记（如皮肤电传导反应）会影响决策过程。尽管该假说很突出，但仍存在争议，部分原因是不恰当的统计方法导致结果不一致。旨在评估决策的任务通常采用重复测量设计，例如爱荷华赌博任务（IGT），该任务要求参与者从四组提供不同输赢可能性的牌组中选择100张牌以实现利润最大化。研究人员经常将重复测量汇总为单个平均值以简化分析，这可能会犯生态谬误，即将从汇总数据（即个体间效应）获得的结果错误地推广到个体重复测量（即个体内效应）。本文通过展示如何使用多层逻辑模型分析自变量和因变量的并发重复测量来解决这个问题。首先，解释逻辑多层模型的原理。然后，分析模拟和实证的IGT数据，以比较传统统计方法（即一般线性模型）与多层逻辑模型的性能。我们提出的多层逻辑分析解决了决策研究中的关键方法学差距，确保对重复测量数据有更准确的解释。这种方法不仅推进了躯体标记假说的研究，还为类似的研究方案提供了一个强大的框架，最终提高了研究结果的可靠性和有效性。
