21 citations · 30 across the 10 of their papers we have counts for
13 papers
DAG-CLIP: A DAG Learning Framework in the Presence of Latent Variables
Siliang Zhang, Yunxiao Chen, Irini Moustaki
Learning directed acyclic graphs (DAGs) to uncover causal mechanisms has attracted substantial attention in machine learning. While most existing methods focus exclusively on obser…
Mental Health Support Hotlines as Capacity-Limited Services: Joint Modeling of Demand, Assessment, and Unassessed Calls
Siliang Zhang, Jing Ouyang
Mental health support hotlines log help-seeking call attempts in real time, yet limited service capacity allows only a small proportion of calls to be answered and assessed. The ti…
A Latent Variable Framework for Multiple Imputation with Non-ignorable Missingness: Analyzing Perceptions of Social Justice in Europe
Siliang Zhang, Yunxiao Chen, Jouni Kuha
This paper proposes a general multiple imputation approach for analyzing large-scale data with missing values. An imputation model is derived from a joint distribution induced by a…
A Note on Ising Network Analysis with Missing Data
Siliang Zhang, Yunxiao Chen
The Ising model has become a popular psychometric model for analyzing item response data. The statistical inference of the Ising model is typically carried out via a pseudo-likelih…
Longitudinal analysis of exchanges of support between parents and children in the UK
Fiona Steele, Siliang Zhang, Emily Grundy +1
We consider how exchanges of support between parents and adult children vary by demographic and socio-economic characteristics and examine evidence for reciprocity in transfers and…
Modelling Correlation Matrices in Multivariate Dyadic Data: Latent Variable Models for Intergenerational Exchanges of Family Support
Siliang Zhang, Jouni Kuha, Fiona Steele
We define a model for the joint distribution of multiple continuous latent variables which includes a model for how their correlations depend on explanatory variables. This is moti…
Adjusting for non-confounding covariates in case-control association studies
Siliang Zhang, Jinbo Chen, Zhiliang Ying +1
There is a considerable literature in case-control logistic regression on whether or not non-confounding covariates should be adjusted for. However, only limited and ad hoc theoret…
Latent variable models for multivariate dyadic data with zero inflation: Analysis of intergenerational exchanges of family support
Jouni Kuha, Siliang Zhang, Fiona Steele
Understanding the help and support that is exchanged between family members of different generations is of increasing importance, with research questions in sociology and social po…
Computation for Latent Variable Model Estimation: A Unified Stochastic Proximal Framework
Siliang Zhang, Yunxiao Chen
Latent variable models have been playing a central role in psychometrics and related fields. In many modern applications, the inference based on latent variable models involves one…
Estimation Methods for Item Factor Analysis: An Overview
Yunxiao Chen, Siliang Zhang
Item factor analysis (IFA) refers to the factor models and statistical inference procedures for analyzing multivariate categorical data. IFA techniques are commonly used in social…
A Latent Gaussian Process Model for Analyzing Intensive Longitudinal Data
Yunxiao Chen, Siliang Zhang
Intensive longitudinal studies are becoming progressively more prevalent across many social science areas, especially in psychology. New technologies like smart-phones, fitness tra…
Structured Latent Factor Analysis for Large-scale Data: Identifiability, Estimability, and Their Implications
Yunxiao Chen, Xiaoou Li, Siliang Zhang
Latent factor models are widely used to measure unobserved latent traits in social and behavioral sciences, including psychology, education, and marketing. When used in a confirmat…
Joint Maximum Likelihood Estimation for High-dimensional Exploratory Item Response Analysis
Yunxiao Chen, Xiaoou Li, Siliang Zhang
Joint maximum likelihood (JML) estimation is one of the earliest approaches to fitting item response theory (IRT) models. This procedure treats both the item and person parameters…