Sociocognitive and Argumentation Perspectives on Psychometric Modeling in Educational Assessment [0.03%]
社会认知和论证视角下的教育测评心理计量模型研究
Robert J Mislevy
Robert J Mislevy
Rapid advances in psychology and technology open opportunities and present challenges beyond familiar forms of educational assessment and measurement. Viewing assessment through the perspectives of complex adaptive sociocognitive systems an...
A Multidimensional Model to Facilitate Within Person Comparison of Attributes [0.03%]
一种多维模型以促进属性的内在比较
Mark L Davison,Seungwon Chung,Nidhi Kohli et al.
Mark L Davison et al.
In psychological research and practice, a person's scores on two different traits or abilities are often compared. Such within-person comparisons require that measurements have equal units (EU) and/or equal origins: an assumption rarely val...
Adjusted Residuals for Evaluating Conditional Independence in IRT Models for Multistage Adaptive Testing [0.03%]
IRT模型中条件独立性的评价方法及其在多阶段自适应测试中的应用研究
Peter W van Rijn,Usama S Ali,Hyo Jeong Shin et al.
Peter W van Rijn et al.
The key assumption of conditional independence of item responses given latent ability in item response theory (IRT) models is addressed for multistage adaptive testing (MST) designs. Routing decisions in MST designs can cause patterns in th...
Regularized Variational Estimation for Exploratory Item Factor Analysis [0.03%]
正则化变分估计在探索性项目因子分析中的应用
April E Cho,Jiaying Xiao,Chun Wang et al.
April E Cho et al.
Item factor analysis (IFA), also known as Multidimensional Item Response Theory (MIRT), is a general framework for specifying the functional relationship between respondents' multiple latent traits and their responses to assessment items. T...
Xinyu Zhang,Xiangbin Meng,Wei Gao et al.
Xinyu Zhang et al.
Uncovering Latent Structures:A Bayesian Approach to Estimating Q-Matrix and Attribute Hierarchies in Cognitive Diagnostic Models [0.03%]
挖掘潜在结构：认知诊断模型中估计Q矩阵和属性层次的贝叶斯方法
Xue Wang,Yinghan Chen,Shiyu Wang
Xue Wang
Philipp Sterzinger,Ioannis Kosmidis,Irini Moustaki
Philipp Sterzinger
Spectral Clustering with Likelihood Refinement for High-dimensional Latent Class Recovery [0.03%]
基于似然精化的谱聚类高维潜在类别恢复方法
Zhongyuan Lyu,Yuqi Gu
Zhongyuan Lyu
The co-varying ties between networks and item responses via latent variables [0.03%]
基于潜变量的网络与题目响应共变关系研究
Selena Wang,Tracy Morrison Sweet,Subhadeep Paul
Selena Wang