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09/20/2023
ddtlcm: An R package for overcoming weak separation in Bayesian latent class analysis via tree-regularization
Traditional applications of latent class models (LCMs) often focus on sc...
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09/14/2023
A joint modeling approach to study the association between subject-level longitudinal marker variabilities and repeated outcomes
Women are at increased risk of bone loss during the menopausal transitio...
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06/29/2023
Incorporating Auxiliary Variables to Improve the Efficiency of Time-Varying Treatment Effect Estimation
The use of smart devices (e.g., smartphones, smartwatches) and other wea...
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06/07/2023
Tree-Regularized Bayesian Latent Class Analysis for Improving Weakly Separated Dietary Pattern Subtyping in Small-Sized Subpopulations
Dietary patterns synthesize multiple related diet components, which can ...
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02/16/2023
Bayesian Active Questionnaire Design for Cause-of-Death Assignment Using Verbal Autopsies
Only about one-third of the deaths worldwide are assigned a medically-ce...
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01/31/2023
A Reinforcement Learning Framework for Dynamic Mediation Analysis
Mediation analysis learns the causal effect transmitted via mediator var...
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12/02/2022
Estimating Time-Varying Direct and Indirect Causal Excursion Effects with Longitudinal Binary Outcomes
Construction of just-in-time adaptive interventions, such as prompts del...
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11/08/2022
Doubly Inhomogeneous Reinforcement Learning
This paper studies reinforcement learning (RL) in doubly inhomogeneous e...
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07/30/2022
Outcome Adaptive Propensity Score Methods for Handling Censoring and High-Dimensionality: Application to Insurance Claims
Propensity scores are commonly used to reduce the confounding bias in no...
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07/15/2022
Variance as a predictor of health outcomes: Subject-level trajectories and variability of sex hormones to predict body fat changes in peri- and post-menopausal women
Longitudinal biomarker data and cross-sectional outcomes are routinely c...
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03/03/2022
Reinforcement Learning in Possibly Nonstationary Environments
We consider reinforcement learning (RL) methods in offline nonstationary...
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02/23/2022
baker: An R package for Nested Partially-Latent Class Models
This paper describes and illustrates the functionality of the baker R pa...
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01/23/2022
Probabilistic Learning of Treatment Trees in Cancer
Accurate identification of synergistic treatment combinations and their ...
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12/22/2021
Bayesian Nested Latent Class Models for Cause-of-Death Assignment using Verbal Autopsies Across Multiple Domains
Understanding cause-specific mortality rates is crucial for monitoring p...
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12/21/2021
Tree-informed Bayesian multi-source domain adaptation: cross-population probabilistic cause-of-death assignment using verbal autopsy
Determining causes of deaths (COD) occurred outside of civil registratio...
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11/02/2021
Dynamic statistical inference in massive datastreams
Modern technological advances have expanded the scope of applications re...
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11/01/2021
Kernel Deformed Exponential Families for Sparse Continuous Attention
Attention mechanisms take an expectation of a data representation with r...
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02/02/2021
Assessing Time-Varying Causal Effect Moderation in the Presence of Cluster-Level Treatment Effect Heterogeneity
Micro-randomized trial (MRT) is a sequential randomized experimental des...
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03/28/2020
A Hierarchical Integrative Group LASSO (HiGLASSO) Framework for Analyzing Environmental Mixtures
Environmental health studies are increasingly measuring multiple polluta...
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03/02/2020
A Functional EM Algorithm for Panel Count Data with Missing Counts
Panel count data is recurrent events data where counts of events are obs...
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02/19/2020
Weakly-supervised Multi-output Regression via Correlated Gaussian Processes
Multi-output regression seeks to infer multiple latent functions using d...
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06/20/2019
Regression Analysis of Dependent Binary Data for Estimating Disease Etiology from Case-Control Studies
In large-scale disease etiology studies, epidemiologists often need to u...
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08/24/2018