16 citations · 58 across the 21 of their papers we have counts for
22 papers
Design-Based Cross-Validation for Comparing Small Area Estimators
Qianyu Dong, Zehang Richard Li
Subnational monitoring of public health and development indicators often relies on household surveys where data are sparse at the desired spatial resolution. Small area estimation…
On Data Thinning for Model Validation in Small Area Estimation
Sho Kawano, Paul A. Parker, Zehang Richard Li
Small area estimation produces estimates of population parameters for geographic and demographic subgroups with limited sample sizes. Such estimates are critical for policy decisio…
Bayesian Federated Cause-of-Death Classification and Quantification Under Distribution Shift
Yu Zhu, Jason Teng, Zehang Richard Li
In regions lacking medically certified causes of death, verbal autopsy (VA) is a widely used tool to ascertain the cause of death through interviews with caregivers. Data collected…
Flexible Bayesian Tensor Decomposition for Verbal Autopsy Data
Yu Zhu, Zehang Richard Li
Cause-of-death data is fundamental for understanding population health trends and inequalities as well as designing and evaluating public health interventions. A significant propor…
Hierarchical Latent Class Models for Mortality Surveillance Using Partially Verified Verbal Autopsies
Yu Zhu, Zehang Richard Li
Monitoring cause-of-death data is an important part of understanding disease burdens and effects of public health interventions. Verbal autopsy (VA) is a well-established method fo…
Bayesian analysis of verbal autopsy data using factor models with age- and sex-dependent associations between symptoms
Tsuyoshi Kunihama, Zehang Richard Li, Samuel J. Clark +1
Verbal autopsies (VAs) are extensively used to investigate the population-level distributions of deaths by cause in low-resource settings without well-organized vital statistics sy…
Treatment Effect Estimation Amidst Dynamic Network Interference in Online Gaming Experiments
Yu Zhu, Zehang Richard Li, Yang Su +1
The evolving landscape of online multiplayer gaming presents unique challenges in assessing the causal impacts of game features. Traditional A/B testing methodologies fall short du…
Bayesian Active Questionnaire Design for Cause-of-Death Assignment Using Verbal Autopsies
Toshiya Yoshida, Trinity Shuxian Fan, Tyler McCormick +2
Only about one-third of the deaths worldwide are assigned a medically-certified cause, and understanding the causes of deaths occurring outside of medical facilities is logisticall…
Tree-informed Bayesian multi-source domain adaptation: cross-population probabilistic cause-of-death assignment using verbal autopsy
Zhenke Wu, Zehang Richard Li, Irena Chen +1
Determining causes of deaths (COD) occurred outside of civil registration and vital statistics systems is challenging. A technique called verbal autopsy (VA) is widely adopted to g…
Bayesian Nested Latent Class Models for Cause-of-Death Assignment using Verbal Autopsies Across Multiple Domains
Zehang Richard Li, Zhenke Wu, Irena Chen +1
Understanding cause-specific mortality rates is crucial for monitoring population health and designing public health interventions. Worldwide, two-thirds of deaths do not have a ca…
The Two Cultures of Prevalence Mapping: Small Area Estimation and Model-Based Geostatistics
Jon Wakefield, Peter A. Gao, Geir-Arne Fuglstad +1
In low- and middle-income countries (LMICs), accurate estimates of subnational health and demographic indicators are critical for guiding policy and identifying disparities. Many i…
The openVA Toolkit for Verbal Autopsies
Zehang Richard Li, Jason Thomas, Eungang Choi +2
Verbal autopsy (VA) is a survey-based tool widely used to infer cause of death (COD) in regions without complete-coverage civil registration and vital statistics systems. In such s…
Estimating Seroprevalence of SARS-CoV-2 in Ohio: A Bayesian Multilevel Poststratification Approach with Multiple Diagnostic Tests
David Kline, Zehang Li, Yue Chu +4
Globally the SARS-CoV-2 coronavirus has infected more than 59 million people and killed more than 1.39 million. Designing and monitoring interventions to slow and stop the spread o…
Space-Time Smoothing of Survey Outcomes using the R Package SUMMER
Zehang Richard Li, Bryan D Martin, Tracy Qi Dong +5
The increasing availability of complex survey data, and the continued need for estimates of demographic and health indicators at a fine spatial and temporal scale, which leads to i…
Verbal Autopsy in Civil Registration and Vital Statistics: The Symptom-Cause Information Archive
Samuel J. Clark, Martin W. Bratschi, Philip Setel +6
The burden of disease is fundamental to understanding, prioritizing, and monitoring public health interventions. Cause of death is required to calculate the burden of disease, but…
Bayesian Joint Spike-and-Slab Graphical Lasso
Zehang Richard Li, Tyler H. McCormick, Samuel J. Clark
In this article, we propose a new class of priors for Bayesian inference with multiple Gaussian graphical models. We introduce fully Bayesian treatments of two popular procedures,…
Quantifying the Contributions of Training Data and Algorithm Logic to the Performance of Automated Cause-assignment Algorithms for Verbal Autopsy
Samuel J. Clark, Zehang Li, Tyler H. McCormick
A verbal autopsy (VA) consists of a survey with a relative or close contact of a person who has recently died. VA surveys are commonly used to infer likely causes of death for indi…
Bayesian factor models for probabilistic cause of death assessment with verbal autopsies
Tsuyoshi Kunihama, Zehang Richard Li, Samuel J. Clark +1
The distribution of deaths by cause provides crucial information for public health planning, response, and evaluation. About 60% of deaths globally are not registered or given a ca…
Using Bayesian latent Gaussian graphical models to infer symptom associations in verbal autopsies
Zehang Richard Li, Tyler H. McCormick, Samuel J. Clark
Learning dependence relationships among variables of mixed types provides insights in a variety of scientific settings and is a well-studied problem in statistics. Existing methods…
An Expectation Conditional Maximization approach for Gaussian graphical models
Zehang Richard Li, Tyler H. McCormick
Bayesian graphical models are a useful tool for understanding dependence relationships among many variables, particularly in situations with external prior information. In high-dim…
InSilicoVA: A Method to Automate Cause of Death Assignment for Verbal Autopsy
Samuel J. Clark, Tyler McCormick, Zehang Li +1
Verbal autopsies (VA) are widely used to provide cause-specific mortality estimates in developing world settings where vital registration does not function well. VAs assign cause(s…
Probabilistic Cause-of-death Assignment using Verbal Autopsies
Tyler H. McCormick, Zehang Li, Clara Calvert +3
In regions without complete-coverage civil registration and vital statistics systems there is uncertainty about even the most basic demographic indicators. In such areas the majori…