反应风格建模的深化：项目反应树的框架演进及应用
The evolution of item response tree modeling for response styles: Framework advancements and applications
董洁源 1刘红云1
作者信息
- 1. 北京师范大学心理学部, 应用实验心理北京市重点实验室, 心理学国家级实验教学示范中心(北京师范大学)
- 折叠
摘要
项目反应树通过将李克特量表作答分解为多个决策节点，为分离和理解反应风格提供了精细框架。近年来，项目反应树框架持续演进，推动了反应风格研究的深化。在节点层面，项目反应树模型不断拓展，从节点内单维结构到节点内多维结构，从节点均为优势过程到尝试引入理想点过程，对作答理论机制的表征方式更加丰富；在作答过程层面，个体间混合建模、作答内路径不确定性建模以及个体内动态建模等对异质性的考察逐步积累，对过程的刻画也愈加深入。基于对关键进展的系统梳理，本文总结出一套递进式建模分析流程，并配套提供相应的R语言实现函数与实证案例。最后，探讨了反应风格建模中两种核心研究视角（控制测量偏差与理解作答过程）以及项目反应树的未来发展方向。
Abstract
Item response tree (IRTree) models offer a refined framework for disentangling and understanding response styles by decomposing Likert-type item responses into multiple decision nodes. The ongoing evolution of the IRTree framework in recent years has greatly advanced response style research. At the node level, the IRTree model has been extended from within-node unidimensional structures to within-node multidimensional structures, and from assuming dominance processes at all nodes to incorporating ideal point processes, thereby providing a richer representation of the theoretical mechanisms underlying item responding. At the response process level, a growing body of research has explored heterogeneity in the response process, including mixture modeling across respondents, modeling of within-response pathway uncertainty, and intraindividual dynamic modeling, which enables increasingly nuanced investigations. Building on a review of these key advances, this article further summarizes a stepwise analytical workflow for IRTree modeling, and provides supporting R functions along with an empirical demonstration. Finally, this article discusses two perspectives on response style modelingcontrolling for measurement bias and gaining insight into the response processand outlines promising directions for future development of IRTree models.关键词
反应风格/项目反应树/李克特量表/项目反应理论Key words
response styles/item response tree/Likert scale/item response theory引用本文复制引用
董洁源,刘红云.反应风格建模的深化：项目反应树的框架演进及应用[EB/OL].(2026-08-19)[2026-08-24].https://chinaxiv.org/abs/202608.00096.学科分类
科学、科学研究
