Tufts University School of Dental Medicine, Boston, MA, USA.
Stat Med. 2011 Apr 30;30(9):1028-43. doi: 10.1002/sim.4217. Epub 2011 Mar 1.
In psychiatric assessment, Item Response Theory (IRT) is a popular tool to formalize the relation between the severity of a disorder and the associated responses to questionnaire items. Practitioners of IRT sometimes make the assumption of normally distributed severities within a population; while convenient, this assumption is often violated when measuring psychiatric disorders. Specifically, there may be a sizable group of respondents whose answers place them at an extreme of the latent trait spectrum. In this article, a zero- and K-inflated mixture model is developed to account for the presence of such respondents. The model is fitted using an expectation-maximization (E-M) algorithm to estimate the percentage of the population at each end of the continuum, concurrently analyzing the remaining 'graded component' via IRT. A method to perform factor analysis for only the graded component is introduced. In assessments of oppositional defiant disorder and conduct disorder, the zero- and K-inflated model exhibited better fit than the standard IRT model.
在精神科评估中，项目反应理论（IRT）是一种将疾病严重程度与问卷项目相关反应联系起来的常用工具。IRT 的实践者有时会假设人群中严重程度呈正态分布；虽然方便，但当测量精神疾病时，这种假设通常会被违反。具体来说，可能有相当一部分受访者的答案将他们置于潜在特质谱的极端。在本文中，开发了零和 K 膨胀混合模型来解释这种受访者的存在。该模型使用期望最大化（E-M）算法进行拟合，以估计连续体每一端的人群百分比，同时通过 IRT 分析剩余的“分级成分”。引入了仅对分级成分进行因子分析的方法。在对立违抗障碍和品行障碍的评估中，零和 K 膨胀模型的拟合度优于标准 IRT 模型。
