不可分解项目反应理论模型:心理测量学的基本测量方法

IF 2.2 4区 心理学 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Journal of Mathematical Psychology Pub Date : 2023-06-01 DOI:10.1016/j.jmp.2023.102772
Vithor Rosa Franco , Jacob Arie Laros , Marie Wiberg
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引用次数: 0

摘要

本文的主要目的是根据Fishburn(1974)提出的不可分解测量理论,提出项目反应理论(IRT)模型。更具体地说,我们的目标是:(i)介绍Rasch模型的理论基础及其与心理物理学效用模型的关系;(ii)简要阐述Fishburn(19741975)提出的测量理论,其中一些理论不需要加性结构;以及(iii)从这些测量理论导出IRT模型以及这些模型的贝叶斯实现。我们还提供了两个实证例子来比较这些IRT模型与真实数据的拟合程度。除了推导新的IRT模型外,我们还讨论了关于模型生成受访者真实得分基本衡量标准的能力的理论解释。该手稿最后对未来的研究和实际意义进行了展望。
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Nondecomposable Item Response Theory models: Fundamental measurement in psychometrics

The main aim of the current paper is to propose Item Response Theory (IRT) models derived from the nondecomposable measurement theories presented in Fishburn (1974). More specifically, we aim to: (i) present the theoretical basis of the Rasch model and its relations to psychophysics’ models of utility; (ii) give a brief exposition on the measurement theories presented in Fishburn (1974, 1975), some of which do not require an additive structure; and (iii) derive IRT models from these measurement theories, as well as Bayesian implementations of these models. We also present two empirical examples to compare how well these IRT models fit to real data. In addition to deriving new IRT models, we also discuss theoretical interpretations regarding the models’ capability of generating fundamental measures of the true scores of the respondents. The manuscript ends with prospects for future studies and practical implications.

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来源期刊
Journal of Mathematical Psychology
Journal of Mathematical Psychology 医学-数学跨学科应用
CiteScore
3.70
自引率
11.10%
发文量
37
审稿时长
20.2 weeks
期刊介绍: The Journal of Mathematical Psychology includes articles, monographs and reviews, notes and commentaries, and book reviews in all areas of mathematical psychology. Empirical and theoretical contributions are equally welcome. Areas of special interest include, but are not limited to, fundamental measurement and psychological process models, such as those based upon neural network or information processing concepts. A partial listing of substantive areas covered include sensation and perception, psychophysics, learning and memory, problem solving, judgment and decision-making, and motivation. The Journal of Mathematical Psychology is affiliated with the Society for Mathematical Psychology. Research Areas include: • Models for sensation and perception, learning, memory and thinking • Fundamental measurement and scaling • Decision making • Neural modeling and networks • Psychophysics and signal detection • Neuropsychological theories • Psycholinguistics • Motivational dynamics • Animal behavior • Psychometric theory
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