89 citations · 455 across the 65 of their papers we have counts for
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Noisy Matrix Completion under Informative Missingness
Xuanyu Chen, Xiaoyue Niu, Gongjun Xu +1
Noisy matrix completion is a fundamental problem in statistical learning and has attracted a substantial amount of interest over the last two decades. In a variety of applications,…
Genetic association testing with multivariate survival phenotypes under interval censoring
Juhee Lee, Kun Xia, Jianrui Zhang +3
Set-based genetic association tests provide a powerful framework for detecting genetic effects on complex traits by jointly analyzing multiple genetic variants. Although set-based…
Conditional-Independence-Regularized Distributional Autoencoders for Mixed-Type Data
Siyuan Tang, Gongjun Xu, Ji Zhu
Mixed-type data containing both numerical and categorical variables arise in many scientific and real-world applications. Existing representation learning and generative modeling a…
Statistical analysis of block structured latent variable models
Chengyu Cui, Gongjun Xu
This paper studies block structured latent variable models, in which observed variables are grouped into distinct blocks based on their relationships with the underlying latent var…
Stochastic Sensitivity Analysis for Matched Observational Studies
Mengqi Lin, Colin B. Fogarty, Gongjun Xu
Sensitivity analysis asks how strong unmeasured confounding needs to be to explain away an observational study's conclusion. The conventional approach in matched studies conducts i…
Theoretical Analysis of Engression and Reverse Markov Engression
Jiaqi Huang, Gongjun Xu, Ji Zhu
Engression is a recently proposed and effective framework for conditional distribution learning. Its multi-step Reverse Markov extension further improves generative flexibility by…
Multidimensional Item Response Theory under General Latent Distributions
Chengyu Cui, Taoyi Chen, Chun Wang +1
Multidimensional item response theory (MIRT) provides an important psychometric framework for modeling how multiple latent traits jointly influence observed item responses. In most…
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…
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…
Unfolding and Fusion: Debiased Inference for Generalized Multilayer Latent Space Models
Zhaozhe Liu, Gongjun Xu, Haoran Zhang
Multilayer networks have become increasingly ubiquitous across diverse scientific fields, yet their inferential theory remains underdeveloped. We propose a flexible latent space mo…
Identifiability and Inference for Generalized Latent Factor Models
Chengyu Cui, Gongjun Xu
Generalized latent factor analysis not only provides a useful latent embedding approach in statistics and machine learning, but also serves as a widely used tool across various sci…
Recurrent Event Analysis with Ordinary Differential Equations
Bo Meng, Weijing Tang, Gongjun Xu +1
This paper introduces a general framework for analyzing recurrent event data by modeling the conditional mean function of the recurrent event process as the solution to an Ordinary…
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)…
Denoising Diffused Embeddings: a Generative Approach for Hypergraphs
Shihao Wu, Junyi Yang, Gongjun Xu +1
Hypergraph data, which capture multi-way interactions among entities, are increasingly prevalent in the big data era. Generating new hyperlinks from an observed, usually high-dimen…
Quantile Mediation Analytics
Canyi Chen, Yinqiu He, Huixia J. Wang +2
Mediation analytics help examine if and how an intermediate variable mediates the influence of an exposure variable on an outcome of interest. Quantiles, rather than the mean, of a…
A General Latent Embedding Approach for Modeling Non-uniform High-dimensional Sparse Hypergraphs with Multiplicity
Shihao Wu, Gongjun Xu, Ji Zhu
Recent research has shown growing interest in modeling hypergraphs, which capture polyadic interactions among entities beyond traditional dyadic relations. However, most existing m…
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,…
High-dimensional Factor Analysis for Network-linked Data
Jinming Li, Gongjun Xu, Ji Zhu
Factor analysis is a widely used statistical tool in many scientific disciplines, such as psychology, economics, and sociology. As observations linked by networks become increasing…
Variational Estimation for Multidimensional Generalized Partial Credit Model
Chengyu Cui, Chun Wang, Gongjun Xu
Multidimensional item response theory (MIRT) models have generated increasing interest in the psychometrics literature. Efficient approaches for estimating MIRT models with dichoto…
Hyperbolic Network Latent Space Model with Learnable Curvature
Jinming Li, Gongjun Xu, Ji Zhu
Network data is ubiquitous in various scientific disciplines, including sociology, economics, and neuroscience. Latent space models are often employed in network data analysis, but…
A Note on Improving Variational Estimation for Multidimensional Item Response Theory
Chenchen Ma, Jing Ouyang, Chun Wang +1
Survey instruments and assessments are frequently used in many domains of social science. When the constructs that these assessments try to measure become multifaceted, multidimens…
Adaptive Bootstrap Tests for Composite Null Hypotheses in the Mediation Pathway Analysis
He Yinqiu, Song Peter X. -K., Xu Gongjun
Mediation analysis aims to assess if, and how, a certain exposure influences an outcome of interest through intermediate variables. This problem has recently gained a surge of atte…
Sufficient and Necessary Conditions for the Identifiability of DINA Models with Polytomous Responses
Mengqi Lin, Gongjun Xu
Cognitive Diagnosis Models (CDMs) provide a powerful statistical and psychometric tool for researchers and practitioners to learn fine-grained diagnostic information about responde…
Incorporating External Risk Information with the Cox Model under Population Heterogeneity: Applications to Trans-Ancestry Polygenic Hazard Scores
Di Wang, Wen Ye, Ji Zhu +5
Polygenic hazard score (PHS) models designed for European ancestry (EUR) individuals provide ample information regarding survival risk discrimination. Incorporating such informatio…