A key question in the developmental sciences is whether developmental differences are quantitative or qualitative. For example, does age increase the speed in processing a task (quantitative differences) or does age affect the way a task is processed (qualitative differences)? Until now, findings in the domain of decision making have been based on the assumption that developmental differences are either quantitative or qualitative. In the current study, we took a different approach in which we tested whether development is best described as being quantitative or qualitative. We administered a judgment version and a choice version of a decision-making task to a developmental sample (n_judgment = 109 and n_choice = 137; M_age = 12.5 years, age range = 9–18). The task, the so-called Gambling Machine Task, required decisions between two options characterized by constant gains and probabilistic losses; these characteristics were known beforehand and thus did not need to be learned from experience. Data were analyzed by comparing the fit of quantitative and qualitative latent variable models, so-called multiple indicator multiple cause (MIMIC) models. Results indicated that individual differences in both judgment and choice tasks were quantitative and pertained to individual differences in “consideration of gains,” that is, to what extent decisions were guided by gains. These differences were affected by age in the judgment version, but not in the choice version, of the task. We discuss implications for theories of decision making and discuss potential limitations and extensions. We also argue that the MIMIC approach is useful in other domains, for example, to test quantitative versus qualitative development of categorization, reasoning, math, and memory.

发展科学中的一个关键问题是发展差异是数量上的还是质量上的。例如，年龄是否会提高处理任务的速度（数量差异），或者年龄是否会影响处理任务的方式（质量差异）？到目前为止，决策领域的发现都基于这样一个假设，即发展差异要么是数量上的，要么是质量上的。在当前的研究中，我们采用了一种不同的方法，我们测试了最好将发展描述为定量还是定性。我们对一个发展样本（n个_判断 = 109和n个_选择 = 137; 中号_时代 = 12.5 岁，年龄范围 = 9-18）。该任务，即所谓的赌博机任务，需要在以恒定收益和概率损失为特征的两个选项之间做出决定；这些特征是事先已知的，因此不需要从经验中学习。通过比较定量和定性潜在变量模型（所谓的多指标多原因（MIMIC）模型）的拟合来分析数据。结果表明，判断和选择任务的个体差异是定量的，与“考虑收益”的个体差异有关，即决策在多大程度上受收益指导。这些差异在判断版本中受年龄影响，但在选择版本中不受年龄影响。我们讨论对决策理论的影响，并讨论潜在的限制和扩展。我们还认为 MIMIC 方法在其他领域很有用，例如，测试分类、推理、数学和记忆的定量与定性发展。