Fluency tasks are among the most common item formats for the assessment of certain cognitive abilities, such as verbal fluency or divergent thinking. A typical approach to the psychometric modeling of such tasks (e.g., Intelligence, 2016, 57, 25) is the Rasch Poisson Counts Model (RPCM; Probabilistic models for some intelligence and attainment tests. Copenhagen: Danish Institute for Educational Research, 1960), in which, similarly to the assumption of (essential) -equivalence in Classical Test Theory, tasks have equal discriminations—meaning that, beyond varying in difficulty, they do not vary in how strongly they are related to the latent variable. In this research, we question this assumption in the case of divergent thinking tasks, and propose instead to use a more flexible 2-Parameter Poisson Counts Model (2PPCM), which allows to characterize tasks by both difficulty and discrimination. We further propose a Bifactor 2PPCM (B2PPCM) to account for local dependencies (i.e., specific/nuisance factors) emerging from tasks sharing similarities (e.g., similar prompts and domains). We reanalyze a divergent thinking dataset (Psychology of Aesthetics, Creativity, and the Arts, 2008, 2, 68) and find the B2PPCM to significantly outperform the 2PPCM, both outperforming the RPCM. Further extensions and applications of these models are discussed.

中文翻译：

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考虑发散思维流畅度测量中的可变任务歧视：2 参数泊松计数模型及其双因子扩展对 Rasch 泊松计数模型的好处示例

流畅性任务是评估某些认知能力（例如语言流畅性或发散性思维）的最常见项目格式之一。此类任务的心理测量建模的典型方法（例如，Intelligence , 2016, 57, 25）是 Rasch Poisson 计数模型（RPCM；一些智力和成就测试的概率模型。哥本哈根：丹麦教育研究所，1960），其中，类似于（基本的）假设- 经典测试理论中的等价性，任务具有相同的歧视——这意味着，除了难度不同之外，它们与潜在变量的相关程度没有变化。在这项研究中，我们在发散思维任务的情况下质疑这一假设，并建议使用更灵活的 2 参数泊松计数模型 (2PPCM)，它允许通过难度和辨别力来表征任务。我们进一步提出了一个双因子 2PPCM (B2PPCM) 来解释从共享相似性（例如，相似的提示和域）的任务中出现的局部依赖性（即，特定/干扰因素）。我们重新分析了一个发散思维数据集（美学、创造力和艺术心理学, 2008, 2, 68) 并发现 B2PPCM 显着优于 2PPCM，两者都优于 RPCM。讨论了这些模型的进一步扩展和应用。