5 papers
Endogeneity-Aware Cognitive Diagnostic Model for Multidomain Ordinal Assessments
Zhiyu Huang, Jing Ouyang, Kai Kang
Multidomain assessment batteries generate ordinal item responses that are often summarized through latent attribute profiles. Conventional cognitive diagnostic models (CDMs) provid…
Beyond Vintage Rotation: Bias-Free Sparse Representation Learning with Oracle Inference
Chengyu Cui, Yunxiao Chen, Jing Ouyang +1
Learning low-dimensional latent representations is a central topic in statistics and machine learning, and rotation methods have long been used to obtain sparse and interpretable r…
Accounting for Measurement Bias: A New Framework for Reliable Country Ranking in Large-Scale Educational Assessments
Jing Ouyang, Yunxiao Chen, Chengcheng Li +1
International Large-scale Assessments (ILSAs), such as the Program for International Student Assessment (PISA) and the Trends in International Mathematics and Science Study (TIMSS)…
Inference on Generalized Latent Variable Models with High-Dimensional Responses and Covariates
Jing Ouyang, Chengyu Cui, Yunxiao Chen +2
Regression models with both high-dimensional responses and covariates have attracted growing attention. Standard multivariate regression models become inadequate when the response…
Statistical Inference for Covariate-Adjusted and Interpretable Generalized Factor Model with Application to Testing Fairness
Jing Ouyang, Chengyu Cui, Kean Ming Tan +1
Latent variable models are popularly used to measure latent factors (e.g., abilities and personalities) from large-scale assessment data. Beyond understanding these latent factors,…