在解释性项目反应模型中模拟逐人项目协变量的非线性效应:探索图和使用平滑函数建模

IF 1.4 4区 心理学 Q3 PSYCHOLOGY, APPLIED Journal of Educational Measurement Pub Date : 2024-07-25 DOI:10.1111/jedm.12410
Sun‐Joo Cho, Amanda Goodwin, Matthew Naveiras, Paul De Boeck
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引用次数: 0

摘要

在阅读教育和心理语言学领域,解释性项目反应模型(EIRM)已被用于研究人的协变量、项目协变量及其交互作用的影响。在实践中,通常假定协变量与项目反应概率的对数变换之间是线性关系。然而,这种线性假设掩盖了协变量在非线性情况下对其范围的不同影响。因此,本文提出了探索性图表,描述了人和项目协变量对二元结果变量的潜在非线性影响。本文还说明了如何使用具有平滑函数的 EIRM 来模拟这些非线性效应。本研究中考察的平滑函数包括连续人员或项目协变量的单变量平滑函数、连续人员和项目协变量的张量乘积平滑函数,以及连续人员协变量和二元项目协变量之间的双变量平滑函数。参数估计使用 mgcv R 软件包,通过最大似然估计法进行。在实证研究中,我们发现了人与项目协变量交互作用的非线性效应,并讨论了其实际意义。此外,我们还在与实证研究相同的条件下,通过模拟研究对参数恢复、模型比较方法和假设检验程序进行了评估。
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Modeling Nonlinear Effects of Person‐by‐Item Covariates in Explanatory Item Response Models: Exploratory Plots and Modeling Using Smooth Functions
Explanatory item response models (EIRMs) have been applied to investigate the effects of person covariates, item covariates, and their interactions in the fields of reading education and psycholinguistics. In practice, it is often assumed that the relationships between the covariates and the logit transformation of item response probability are linear. However, this linearity assumption obscures the differential effects of covariates over their range in the presence of nonlinearity. Therefore, this paper presents exploratory plots that describe the potential nonlinear effects of person and item covariates on binary outcome variables. This paper also illustrates the use of EIRMs with smooth functions to model these nonlinear effects. The smooth functions examined in this study include univariate smooths of continuous person or item covariates, tensor product smooths of continuous person and item covariates, and by‐variable smooths between a continuous person covariate and a binary item covariate. Parameter estimation was performed using the mgcv R package through the maximum penalized likelihood estimation method. In the empirical study, we identified a nonlinear effect of the person‐by‐item covariate interaction and discussed its practical implications. Furthermore, the parameter recovery and the model comparison method and hypothesis testing procedures presented were evaluated via simulation studies under the same conditions observed in the empirical study.
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来源期刊
CiteScore
2.30
自引率
7.70%
发文量
46
期刊介绍: The Journal of Educational Measurement (JEM) publishes original measurement research, provides reviews of measurement publications, and reports on innovative measurement applications. The topics addressed will interest those concerned with the practice of measurement in field settings, as well as be of interest to measurement theorists. In addition to presenting new contributions to measurement theory and practice, JEM also serves as a vehicle for improving educational measurement applications in a variety of settings.
期刊最新文献
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