The EM Algorithm and Its Variants in Cognitive Diagnostic Models: Comparing Their Propensity for Boundaries, Extremes, Convergence, and Suboptimal Solutions [0.03%]
EM算法及其变体在认知诊断模型中的应用：趋向边界、极端、收敛和次优解的倾向性比较
Yue Zhao,Tao Xin,Yanlou Liu et al.
Yue Zhao et al.
Choosing suitable estimation methods for cognitive diagnostic models (CDMs) is critical. However, practitioners often face issues like non-convergence, boundary estimates, extreme values, and unstable suboptimal solutions, which affect the ...
When Perceptions of Social Desirability Differ: Implications for the Multidimensional Nominal Response Model of Faking [0.03%]
当社会期望感知不同时：关于伪装的多维名义响应模型的启示
Julius David Kleinbub,Timo Seitz
Julius David Kleinbub
Self-report questionnaires are widely used in research and practice. In most applications, the vulnerability of these questionnaires to response biases like faking is ignored. However, especially in high-stakes situations such as personnel ...
Confirmatory Factor Analysis with Adaptive Quadrature Estimator Using Four Link Functions [0.03%]
四种连接函数下的确认性因素分析自适应求积估计方法
Kubra Atalay Kabasakal,Ismail Dilek,Burcu Atar
Kubra Atalay Kabasakal
This study aims to examine the performance of adaptive quadrature (AQ) estimation method for ordinal confirmatory factor analysis (CFA). Specifically, we compared four link functions (complimentary log-log [CLL], logit, log-log, and probit)...
Automatic Item Generation Measurement Models Respecting the Stochastic Sampling Space for Cross-Classified and Two-Level Sampling of Subjects and Incidentals [0.03%]
自动项目生成测量模型尊重跨分类和两级抽样的随机抽样空间主体和偶然性
Philipp Jahn,David Jendryczko,Fridtjof W Nussbeck
Philipp Jahn
In Automatic Item Generation (AIG), item incidentals refer to surface characteristics of an item that are assumed not to influence item parameters (e.g., item difficulty), whereas item radicals refer to attributes that are presumed to affec...
Multistage Testing for Cognitive Diagnosis Based on Skill-Space Partitioning [0.03%]
基于技能空间划分的认知诊断多阶段测试
Rae Yeong Kim,Yun Joo Yoo
Rae Yeong Kim
The growing demand for personalized online learning underscores the necessity for diagnostic assessments that are tailored to the cognitive abilities of individual examinees. The combination of cognitive diagnostic models (CDMs) with comput...
Examining the accuracy of orthogonal latent mean comparisons in unbalanced conditions [0.03%]
检验正交潜均值比较在不平衡条件下的准确性
Jay B Jeffries,James A Bovaird
Jay B Jeffries
Researchers understand that conducting numerous pairwise comparisons between group means increases the Type I error rate, prompting the use of planned contrasts like orthogonal contrast sets. Implicit to orthogonal contrast sets is the prin...
Accounting for CAT-Induced Dependency in Differential Item Functioning Detection: A Multilevel Modeling Framework [0.03%]
基于多层次建模框架的CAT引起的依赖效应在项目功能差异检测中的校正研究
Dandan Danielle Chen Kaptur,Justin L Kern,Chingwei David Shin et al.
Dandan Danielle Chen Kaptur et al.
Differential item functioning (DIF) detection is an important yet understudied problem in computerized adaptive testing (CAT). In this article, we proposed a two-level logistic model to improve DIF detection in CAT by explicitly accounting ...
AllTestSim: Comprehensive Software Tool for Simulating Fixed-Form, Linear-on-the-Fly, Multistage, and Computerized Adaptive Testing [0.03%]
全测试模拟系统：用于仿真固定形式测试、线性飞行测试、多阶段测试和计算机化适应性测试的全面软件工具
Kyung Chris T Han
Kyung Chris T Han
Multidimensional Polytomous DIF Detection Methods - A Monte Carlo Simulation Study [0.03%]
多维多项分类DIF检测方法的一种蒙特卡罗模拟研究
Ana Ćosić Pilepić,Tamara Mohorić,Vladimir Takšić
Ana Ćosić Pilepić
The study compared the effectiveness of four methods for detecting differential item functioning (DIF) in polytomous multidimensional data with a simple structure: the item response theory likelihood ratio test (IRT-LR), two ordinal logisti...