papers

Papers at a glance

Some papers are not listed here. See Google Scholar for a complete list.

Theory/Methods 56

Generalized Fitted Q-Iteration With Clustered Data

Hu et al. (2025). Stat.

PyCFRL: A Python library for counterfactually fair offline reinforcement learning via sequential data preprocessing

Zhang et al. (2026). Journal of Open Source Software.

A Distribution Mapping Approach to Counterfactually Fair Reinforcement Learning

Zhang et al. (submitted).

Bayesian Joint Modeling of Longitudinal Symptomatology Scale Responses and Fall Outcomes via Heterogeneous Latent Transition Analysis

Yu et al. (submitted).

A Multimodal Benchmark for Evaluating Cause-of-Death Inference Using Child Health and Mortality Data

Yang et al. (submitted).

Dynamic Prediction of Alternating Recurrent Events via Neural Network

Loe, Murray and Wu. (submitted).

Neural Networks as Linear Regression: An Introduction for Statisticians

Loe, Murray and Wu. (submitted).

Sparse Longitudinal Functional Principal Component Analysis for Episodic Ambulatory Behavioral Assessments

Pai et al. (submitted).

Joint Modeling of Multiple Longitudinal Biomarkers and Survival Outcomes via Threshold Regression: Variability as a Predictor

Yu et al. (2026). Biometrics.

Prediction-based Inference in Electronic Health Record (EHR)-linked Biobanks with Clinically Informative Outcomes

Chen et al. (submitted).

Spatially Robust Inference with Predicted and Missing at Random Labels

Salerno et al. (submitted).

A joint modeling approach to study the association between subject-level longitudinal marker variabilities and repeated outcomes

Chen et al. (2025). Journal of Applied Statistics.

A Random Forest Inverse Probability Weighted Pseudo-Observation Framework for Alternating Recurrent Events.

Loe, Murray and Wu. (submitted).

Beyond Average Value Function in Precision Medicine: Maximum Probability-Driven Reinforcement Learning for Survival Analysis

Feng et al. (2025). NeurIPS.

A Unified Framework for Inference with General Missingness Patterns and Machine Learning Imputation

Chen et al. (submitted).

Tree-Regularized Bayesian Latent Class Analysis for Improving Weakly Separated Dietary Pattern Subtyping in Small-Sized Subpopulations

Li, Stephenson, Wu (2025). Annals of Applied Statistics.

Incorporating Auxiliary Variables to Improve the Efficiency of Time-Varying Treatment Effect Estimation

Shi, Wu and Dempsey (2025). Journal of American Statistical Association.

Generating Synthetic Electronic Health Record (EHR) Data: A Methodological Scoping Review with Benchmarking on Phenotype Data and Open-Source Software

Chen et al. (2025). Journal of the American Medical Informatics Association.

Random Forest for Dynamic Risk Prediction of Recurrent Events: A Pseudo-Observation Approach

Loe, Murray and Wu. (2025). Biostatistics.

Testing Stationarity and Change Point Detection in Reinforcement Learning

Li et al. (2025). Annals of Statistics.

Counterfactually Fair Reinforcement Learning via Sequential Data Preprocessing

Wang et al. (submitted).

Multivariate Dynamic Mediation Analysis under a Reinforcement Learning Framework

Luo et al. (2025). Annals of Statistics.

Outcome Adaptive Propensity Score Methods for Handling Censoring and High-Dimensionality: Application to Insurance Claims

Du et al. (2025). Statistical Methods in Medical Research.

A Bayesian Approach to Modeling Variance of Intensive Longitudinal Biomarker Data as a Predictor of Health Outcomes

Yu et al. (2024). Statistics in Medicine.

ddtlcm: An R package for overcoming weak separation in Bayesian latent class analysis via tree-regularization

Li, Wu, Stephenson, Wu (2024). Journal of Open Source Software.

Dynamic Statistical Inference in Massive Datastreams

Wang et al. (2024). Statistica Sinica.

Geometry-driven Bayesian Inference for Ultrametric Covariance Matrices

Yao et al. (submitted).

Variance as a predictor of health outcomes:using subject-level trajectories and variability of sex hormones to predict body fat changes in peri- and post-menopausal women

Chen et al. (2024). Annals of Applied Statistics.

Tree-informed Bayesian multi-source domain adaptation: cross-population probabilistic cause-of-death assignment using verbal autopsy

Wu et al. (2024). Biostatistics.

Bayesian Nested Latent Class Models for Cause-of-Death Assignment using Verbal Autopsies Across Multiple Domains

Li et al. (2024). Annals of Applied Statistics.

A Reinforcement Learning Framework for Dynamic Mediation Analysis

Ge et al. (2023). ICML.

A Robust Test for the Stationarity Assumption in Sequential Decision Making

Wang et al. (2023). ICML.

Bayesian Active Questionnaire Design for Cause-of-Death Assignment Using Verbal Autopsies

Yoshida et al. (2023). Conference on Health, Inference, and Learning (CHIL).

Estimating Time-Varying Direct and Indirect Causal Excursion Effects with Longitudinal Binary Outcomes

Shi, Wu and Dempsey (submitted).

Doubly Inhomogeneous Reinforcement Learning

Hu et al. (submitted).

Dynamic Survival Transformers for Causal Inference with Electronic Health Records

Chatha et al. (2022). NeurIPS Workshop.

Assessing Time-Varying Causal Effect Moderation in the Presence of Cluster-Level Treatment Effect Heterogeneity and Interference

Shi, Wu and Dempsey (2022). Biometrika.

Probabilistic Learning of Treatment Trees in Cancer

Yao et al. (2022). Annals of Applied Statistics.

Kernel Multimodal Continuous Attention

Moreno et al. (2022). NeurIPS.

Weakly-supervised Multi-output Regression via Correlated Gaussian Processes

Chung, Kontar, Wu (2022). INFORMS Journal on Data Science.

baker: An R package for Nested Partially-Latent Class Models

Chen et al. (submitted).

Integrating Sample Similarities into Latent Class Analysis: A Tree-Structured Shrinkage Approach

Li et al. (2021). Biometrics.

A Hierarchical Integrative Group LASSO (HiGLASSO) Framework for Analyzing Environmental Mixtures

Boss et al. (2021). Environmetrics.

Probabilistic Cause-of-disease Assignment using Case-control Diagnostic Tests: A Hierarchcial Bayesian Latent Variable Regression Approach

Wu and Chen (2020). Statistics in Medicine.

A Robust Functional EM Algorithm for Incomplete Panel Count Data

Moreno et al. (2020). NeurIPS.

A Bayesian Approach to Restricted Latent Class Models for Scientifically-Structured Clustering of Multivariate Binary Outcomes

Wu et al. (2020). Biometrics.

Bayesian Weakly-Supervised Restricted Latent Class Models

Wu et al. (2020).

Assessing Real-Time Moderation for Developing Adaptive Mobile Health Interventions for Medical Interns - A Micro-randomized Trial

NeCamp et al. (2020). Journal of Medical Internet Research.

Micro-Randomized Trial

Xu, Wu and Murphy (2018). Wiley StatsRef: Statistics Reference Online.

Estimating AutoAntibody Signatures to Detect Autoimmune Disease Patient Subsets

Wu et al. (2017). Biostatistics.

Predicting Survival Time for Metastatic Castration Resistant Prostate Cancer; An Iterative Imputation Approach

Deng et al. (2016). F1000Research.

Nested Partially-Latent Class Models for Dependent Binary Data; Estimating Disease Etiology

Wu et al. (2016) (2016). Biostatistics.

Rejoinder to "Deductive Derivation and Turing-Computerization of Semiparametric Efficient Estimation"

Frangakis et al. (2015). Biometrics.

Deductive Derivation and Turing-Computerization of Semiparametric Efficient Estimation

Frangakis et al. (2015). Biometrics.

Partially Latent Class Models for Case–Control Studies of Childhood Pneumonia Aetiology

Wu et al. (2015). Journal of Royal Statistical Society: Series C (Applied Statistics).

Estimation of Treatment Effects in Matched-Pair Cluster Randomized Trials by Calibrating Covariate Imbalance between Clusters

Wu et al. (2014). Biometrics.

Substantive 37

Patterns of smartphone typing performance by time awake in US training physicians: implications for unobtrusive ambulatory mental fatigue assessment

Fang et al. (2026). PLoS Digital Health.

Extreme Rainfall Modifies the Association between Piped Water Intermittency and Water Quality in Low-Resource Settings

Sosa-Moreno et al. (2026). ACS ES&T Water.

Understanding the Impact of Perceived App Usability on the Efficacy of Mobile Health Intervention for Traumatic Brain Injury Caregivers

Wang et al. (2026). Rehabilitation Psychology.

Depression symptoms among Kenyan healthcare workers and associated factors

Aballa et al. (2025). JAMA Psychiatry.

Completion and Compliance Rates for an Intensive mHealth Study Design to Promote Self-Awareness and Self-Care Among Care Partners of Individuals With Traumatic Brain Injury: Data From a Randomized Controlled Trial

Carlozzi et al. (2025). JMIR mHealth and uHealth.

Comparing the Power of Low vs High-Precision Methods for Measuring E. coli in Drinking Water in Low-Resource Settings

Sosa-Moreno et al. (2025). ACS ES&T Water.

Clinician attitudes, opinions and practice patterns regarding inotrope use for cardiac surgery in the USA: a multicentre mixed methods study protocol

Mathis et al. (2025). BMJ Open.

Improving outcomes for care partners of individuals with traumatic brain injury: Results for a mHealth randomized control trial of the CareQOL app

Carlozzi et al. (2025). Archives of Physical Medicine and Rehabilitation.

Pediatric urinary tract infections caused by poultry-associated Escherichia coli

Aziz et al. (2024). Microbiology Spectrum.

Etiology of acute lower respiratory illness hospitalizations among infants in four countries

Kubale et al. (2023). Open Forum Infectious Diseases.

Does the Dosing of Mobile-based Just-in-Time-Adaptive Self-Management Prompts Matter? Preliminary Findings from a Pilot Micro-Randomized Study for Caregivers

Wang et al. (2023). JMIR Formative Research.

An Automatically-Adaptive Digital Health Intervention to Decrease Opioid-Related Risk While Conserving Counselor Time: Analysis of Treatment Decisions Based on Artificial Intelligence and Patient-Reported Risk Measures

Piette et al. (2023). Journal of Medical Internet Research.

Identifying Design Opportunities for Adaptive mHealth Interventions That Target General Well-Being: Interview Study With Informal Care Partners

Yan et al. (2023). JMIR Formative Research.

Feasibility pilot trial for the Trajectories of Recovery after Intravenous propofol versus inhaled VolatilE anesthesia (THRIVE) Pragmatic Randomized Controlled Trial

Pennington et al. (2023). BMJ Open.

Using source-associated mobile genetic elements to identify zoonotic extraintestinal E. coli infections

Liu et al. (2023). One Health.

Layperson-Facilitated Internet-Delivered Cognitive Behavioral Therapy for Homebound Older Adults with Depression: Protocol for a Randomized Controlled Trial

Kayser et al. (2023). JMIR Research Protocol.

A Caveat to Using Wearable Sensor Data for COVID-19 Detection: The Role of Behavioral Change after Receipt of Test Results

Cleary et al. (2022). PLOS ONE.

Using machine learning with intensive longitudinal data to predict depression and suicidal ideation among medical interns over time

Horwitz et al. (2022). Psychological Medicine.

Effectiveness of gamified competition in the context of mHealth intervention for medical interns: a clustered micro-randomized trial

Wang et al. (2022). Nature Digital Medicine.

An App-Based Just-in-Time-Adaptive Self-Management Intervention for Care Partners: The CareQOL Feasibility Pilot Study

Carlozzi et al. (2022). Rehabilitation Psychology.

Parental preferences for STI and cancer vaccines in the US and in China

Wagner et al. (2022). Value in Health.

Improving outcomes for care partners of persons with traumatic brain injury: Protocol for a randomized control trial of a just-in-time-adaptive self-management intervention

Carlozzi et al. (2022). PLOS ONE.

Vaccine hesitancy during the COVID-19 pandemic: a latent class analysis of middle-aged and older US adults

Wagner et al. (2022). Journal of Community Health.

Factors associated with inferior vena cava placement and retrieval for patients with cancer associated thrombosis

Edupuganti et al. (2021). The American Journal of Medicine.

Acceptability and feasibility of an app-based just-in-time-adaptive self-management intervention for care partners: Protocol for the CareQOL pilot trial

Carlozzi et al. (2021). JMIR Research Protocol.

The Mobile Assistance for Regulating Smoking (MARS) Micro-Randomized Trial Design Protocol

Nahum-Shani et al. (2021). Contemporary Clinical Trials.

Clinical and Sociodemographic Factors Associated with Anticoagulant Use for Cancer Associated Thrombosis.

Schaefer et al. (2020). Journal of Thrombosis and Thrombolysis.

Using a Bayesian Approach to Predict Patients’ Health and Response to Treatment

Zeger SL, Wu Z, Coley Y, et al. (2020). Patient-Centered Outcomes Research Institute (PCORI).

Anticoagulant Medication Adherence for Cancer Associated Thrombosis: A Comparison of LMWH to DOACs

Schaefer et al. (2020). Journal of Thrombosis and Haemostasis.

Modern Senicide in the Face of a Pandemic: An Examination of Public Discourse and Sentiment about Older Adults and COVID-19 Using Machine Learning.

Xiang et al. (2020). Journals of Gerontology: Series B.

Characterization of clinical progression of COVID-19 patients in Shenzhen, China

Bi et al. (2020). medRxiv.

Computational Analysis of Continuous Body Temperature Provides Early Discrimination of Graft-versus-Host Disease in Mice

Kuang et al. (2019). Blood Advances.

Causes of severe pneumonia requiring hospital admission in children without HIV infection from Africa and Asia: the PERCH multi-country case-control study

PERCH Study Group (2019). The Lancet.

Association of Polygenic Risk Scores for Multiple Cancers in a Phenome-wide Study Results from The Michigan Genomics Initiative

Fritsche et al. (2018). American Journal of Human Genetics.

Bayesian Estimation of Pneumonia Etiology: Epidemiologic Considerations and Applications to the Pneumonia Etiology Research for Child Health Study

Deloria-Knoll et al. (2017). Clinical Infectious Diseases.

Prediction of overall survival for patients with metastatic castration-resistant prostate cancer; development of a prognostic model through a crowdsourced challenge with open clinical data

Guinney et al. (2017). The Lancet Oncology.

Lack of Response after Initial Chemoembolization for Hepatocellular Carcinoma: Does It Predict Failure of Subsequent Treatment?

Georgiades et al. (2012). Radiology.