A Bayesian framework for the logistic positive exponent and its reflection IRT models [0.03%]
逻辑正指数和其反向项目响应模型的贝叶斯分析框架
Jorge González,Jorge Bazán,Isidora Colil-Celis
Jorge González
The logistic positive exponent (LPE) and its reflection (RLPE) models accommodate asymmetric item characteristic curves in item response theory, offering greater flexibility than traditional symmetric specifications. While several asymmetri...
Yang Liu,Jonathan P Williams,Jan Hannig
Yang Liu
Bayesian statistics has gained popularity in psychological research due to its intuitive uncertainty quantification and convenient information-updating rules. In many applications, however, prior distributions are introduced merely as instr...
Multidimensional unipolar IRT and applications to the measurement of print exposure [0.03%]
多维单极性IRT及其在印刷曝光测量中的应用
Qi Helen Huang,Daniel M Bolt
Qi Helen Huang
Item response theory (IRT) has been a prominent modelling framework in educational and psychological measurement. Traditional IRT models are bipolar, commonly assuming symmetric measurement link functions and symmetric trait distributions o...
On the asymmetry, complexity and predicted data patterns of nontraditional item response theory models [0.03%]
非传统项目反应理论模型的不对称性、复杂性和预测数据模式
Hyejin Shim,Wes Bonifay
Hyejin Shim
Traditional item response theory (IRT) models involve symmetric response probability functions, but a developing area of research has focused on asymmetric alternatives. To date, these studies have focused primarily on introducing new asymm...
Estimation of comparable standardized mean differences in cluster randomized trials with covariate adjustment [0.03%]
协变量调整的分组随机试验中的可比标准化均值差估计方法研究
Juyoung Jung,Zhijiang Liu,Ariel M Aloe
Juyoung Jung
Standardized mean differences (SMDs) are widely used to quantify treatment effects in cluster-randomized trials. However, covariate adjustment in hierarchical linear models reduces the residual variance components used for standardization, ...
Revisiting reliability and measurement precision: Towards a unified perspective [0.03%]
重新审视可靠性和测量精确性：迈向统一的视角
Jimmy de la Torre,Klaas Sijtsma,Rodrigo Schames Kreitchmann
Jimmy de la Torre
This article revisits the concepts of reliability and measurement precision across classical test theory (CTT), item response theory (IRT) and cognitive diagnosis models (CDMs), emphasizing their conceptual differences and proposing a unifi...
Elena Castilla
Elena Castilla
This paper introduces a new class of estimators for cognitive diagnosis models (CDMs) based on the Cressie-Read family of ϕ $$ /phi $$ -divergences. Focusing on the loglinear CDM (LCDM), for which joint maximum likelihood estimation ...
Andres F Perez Alonso,Jeroen K Vermunt,Yves Rosseel et al.
Andres F Perez Alonso et al.
Social scientists often compare groups in terms of relations between latent variables (LV) (i.e. structural relations) using Structural Equation Modelling (SEM). LVs are measured indirectly by questionnaires; thus, measurement invariance mu...
Review of cognitive diagnostic models (CDMs): Recent methodological advancements for addressing practical challenges [0.03%]
认知诊断模型研究进展：应对实际挑战的方法论创新
Chun Wang,Yale Quan,David Arthur
Chun Wang
Cognitive diagnostic models (CDMs) have become essential tools for providing fine-grained information about individuals' mastery of cognitive skills. While prior reviews have emphasized statistical foundations and deep learning-based develo...
Refining effect size measures and classification for differential item functioning: Toward unified guidelines across methods [0.03%]
精炼差异项目功能效应量衡量标准和分类：跨方法统一指南的实证基础
Michaela Cichrová,Adéla Hladká,Patrícia Martinková
Michaela Cichrová
Differential Item Functioning (DIF) analysis is used to identify potentially biased items in multi-item measurements. In addition to testing the statistical significance, it is essential to evaluate the practical significance of DIF through...