Psychological Methods 提出用于纵向评估的时变交互图方法

We introduce a novel approach to analyzing responses of individuals to items at two or more time points. Existing longitudinal item response models do not capture interactions among individuals and items that evolve over time. We construct time-varying interaction maps with a view to capturing and visualizing time-varying interactions among individuals and items in a low-dimensional Euclidean space. A time-varying interaction map provides a window into the strengths and weaknesses of an individual on specific items, in addition to tracking changes in the underlying trait of the individual. We provide a data-driven Bayesian approach to determining whether time-varying interaction maps have added value, along with Bayesian methods for learning time-varying interaction maps from observed responses. We present multiple simulation and empirical studies to showcase the merits of time-varying interaction maps, including applications to behavior ratings of children and problem-solving assessments of students. (PsycInfo Database Record (c) 2026 APA, all rights reserved)

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