A Note on Standard Errors for Multidimensional Two-Parameter Logistic Models Using Gaussian Variational Estimation [0.03%]
有关使用高斯变分估计的多维二参数逻辑模型标准误差的注记
Jiaying Xiao,Chun Wang,Gongjun Xu
Jiaying Xiao
Accurate item parameters and standard errors (SEs) are crucial for many multidimensional item response theory (MIRT) applications. A recent study proposed the Gaussian Variational Expectation Maximization (GVEM) algorithm to improve computa...
Using Interpretable Machine Learning for Differential Item Functioning Detection in Psychometric Tests [0.03%]
使用可解释机器学习进行心理测量测试中的项目功能差异检测
Elisabeth Barbara Kraus,Johannes Wild,Sven Hilbert
Elisabeth Barbara Kraus
This study presents a novel method to investigate test fairness and differential item functioning combining psychometrics and machine learning. Test unfairness manifests itself in systematic and demographically imbalanced influences of conf...
aberrance: An R Package for Detecting Aberrant Behavior in Test Data [0.03%]
异常行为检测：一种测试数据中的异常行为检测R包——ABERRANCE
Kylie Gorney,Jiayi Deng
Kylie Gorney
Investigating Directional Invariance in an Item Response Tree Model for Extreme Response Style and Trait-Based Unfolding Responses [0.03%]
极端回应风格和特质展开反应下的项目响应树模型的导向不变性研究
Siqi He,Justin L Kern
Siqi He
Item response tree (IRTree) approaches have received increasing attention in the response style literature due to their capability to partial out response style latent traits from content-related latent traits by considering separate decisi...
Accommodating and Extending Various Models for Special Effects Within the Generalized Partially Confirmatory Factor Analysis Framework [0.03%]
广义部分确认因子分析框架下包容和拓展各种模型以产生特殊效应
Yifan Zhang,Jinsong Chen
Yifan Zhang
Special measurement effects including the method and testlet effects are common issues in educational and psychological measurement. They are typically covered by various bifactor models or models for the multiple traits multiple methods (M...
How Scoring Approaches Impact Estimates of Growth in the Presence of Survey Item Ceiling Effects [0.03%]
赋分方法对顶限效应存在下增长估计的影响分析
Kelly D Edwards,James Soland
Kelly D Edwards
Survey scores are often the basis for understanding how individuals grow psychologically and socio-emotionally. A known problem with many surveys is that the items are all "easy"-that is, individuals tend to use only the top one or two resp...
Detecting Differential Item Functioning in Multidimensional Graded Response Models With Recursive Partitioning [0.03%]
基于递归划分的多维逐级反应模型项目功能差异检测方法研究
Franz Classe,Christoph Kern
Franz Classe
Differential item functioning (DIF) is a common challenge when examining latent traits in large scale surveys. In recent work, methods from the field of machine learning such as model-based recursive partitioning have been proposed to ident...
Linking Methods for Multidimensional Forced Choice Tests Using the Multi-Unidimensional Pairwise Preference Model [0.03%]
基于多维度配对偏好模型的多维强制选择测验链结方法研究
Naidan Tu,Lavanya S Kumar,Sean Joo et al.
Naidan Tu et al.
Applications of multidimensional forced choice (MFC) testing have increased considerably over the last 20 years. Yet there has been little, if any, research on methods for linking the parameter estimates from different samples. This researc...
Evaluating the Douglas-Cohen IRT Goodness of Fit Measure With BIB Sampling of Items [0.03%]
利用BIB项目抽样评价Douglas-Cohen IRT拟合优度指标
John R Donoghue,Adrienne Sgammato
John R Donoghue
Methods to detect item response theory (IRT) item-level misfit are typically derived assuming fixed test forms. However, IRT is also employed with more complicated test designs, such as the balanced incomplete block (BIB) design used in lar...
Location-Matching Adaptive Testing for Polytomous Technology-Enhanced Items [0.03%]
多级题型的计算机化自适应测验中的题目位置匹配算法研究
Hyeon-Ah Kang,Gregory Arbet,Joe Betts et al.
Hyeon-Ah Kang et al.
The article presents adaptive testing strategies for polytomously scored technology-enhanced innovative items. We investigate item selection methods that match examinee's ability levels in location and explore ways to leverage test-taking s...