399 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Rice UniversityUS17 papers
- The University of Texas Health Science Center at HoustonUS17 papers
- The University of Texas at AustinUS13 papers
- Harvard UniversityUS12 papers
- Baylor College of MedicineUS10 papers
- The University of Texas Southwestern Medical CenterUS9 papers
- University of PennsylvaniaUS8 papers
- Massachusetts General HospitalUS7 papers
- Stanford UniversityUS7 papers
- Technical University of MunichDE7 papers
- University of Alabama at BirminghamUS7 papers
- University of North Carolina at Chapel HillUS7 papers
38 papers · 1 filter
Bayesian Clustering Prior with Overlapping Indices for Effective Use of Multisource External Data
Xuetao Lu, J. Jack Lee
The use of external data in clinical trials offers numerous advantages, such as reducing the number of patients, increasing study power, and shortening trial durations. In Bayesian…
Bayesian Transfer Learning for Enhanced Estimation and Inference
Daoyuan Lai, Oscar Hernan Madrid Padilla, Xiang Li +1
Transfer learning enhances model performance in a target population with limited samples by leveraging knowledge from related studies. While many works focus on improving predictiv…
Clustering Computer Mouse Tracking Data with Informed Hierarchical Shrinkage Partition Priors
Ziyi Song, Weining Shen, Marina Vannucci +4
Mouse-tracking data, which record computer mouse trajectories while participants perform an experimental task, provide valuable insights into subjects' underlying cognitive process…
ROMI: A Randomized Two-Stage Basket Trial Design to Optimize Doses for Multiple Indications
Shuqi Wang, Peter F. Thall, Kentaro Takeda +1
Optimizing doses for multiple indications is challenging. The pooled approach of finding a single optimal biological dose (OBD) for all indications ignores that dose-response or do…
Conformal predictive intervals in survival analysis: a re-sampling approach
Jing Qin, Jin Piao, Jing Ning +1
The distribution-free method of conformal prediction (Vovk et al, 2005) has gained considerable attention in computer science, machine learning, and statistics. Candes et al. (2023…
A Weibull Mixture Cure Frailty Model for High-dimensional Covariates
Fatih Kızılaslan, David Michael Swanson, Valeria Vitelli
A novel mixture cure frailty model is introduced for handling censored survival data. Mixture cure models are preferable when the existence of a cured fraction among patients can b…
A reluctant additive model framework for interpretable nonlinear individualized treatment rules
Jacob M. Maronge, Jared D. Huling, Guanhua Chen
Individualized treatment rules (ITRs) for treatment recommendation is an important topic for precision medicine as not all beneficial treatments work well for all individuals. Inte…
Separable effects for adherence
Kerollos Nashat Wanis, Mats Julius Stensrud, Aaron Leor Sarvet
Comparing different medications is complicated when adherence to these medications differs. We can overcome the adherence issue by assessing effectiveness under sustained use, as i…
Overlapping Indices for Dynamic Information Borrowing in Bayesian Hierarchical Modeling
Xuetao Lu, J. Jack Lee
Bayesian hierarchical model (BHM) has been widely used in synthesizing information across subgroups. Identifying heterogeneity in the data and determining proper strength of borrow…
Grace periods in comparative effectiveness studies of sustained treatments
Kerollos Nashat Wanis, Aaron L. Sarvet, Lan Wen +4
Researchers are often interested in estimating the effect of sustained use of a treatment on a health outcome. However, adherence to strict treatment protocols can be challenging f…
Efficient Targeted Learning of Heterogeneous Treatment Effects for Multiple Subgroups
Waverly Wei, Maya Petersen, Mark J van der Laan +3
In biomedical science, analyzing treatment effect heterogeneity plays an essential role in assisting personalized medicine. The main goals of analyzing treatment effect heterogenei…
Knowledge Distillation Decision Tree for Unravelling Black-box Machine Learning Models
Xuetao Lu, J. Jack Lee
Machine learning models, particularly the black-box models, are widely favored for their outstanding predictive capabilities. However, they often face scrutiny and criticism due to…
A Convex-Nonconvex Strategy for Grouped Variable Selection
Xiaoqian Liu, Aaron J. Molstad, Eric C. Chi
This paper deals with the grouped variable selection problem. A widely used strategy is to augment the negative log-likelihood function with a sparsity-promoting penalty. Existing…
Flexible Bayesian Product Mixture Models for Vector Autoregressions
Suprateek Kundu, Joshua Lukemire
Bayesian non-parametric methods based on Dirichlet process mixtures have seen tremendous success in various domains and are appealing in being able to borrow information by cluster…
Augmenting control arms with Real-World Data for cancer trials: Hybrid control arm methods and considerations
W. Katherine Tan, Brian D. Segal, Melissa D. Curtis +9
Randomized controlled trials (RCTs) are the gold standard for assessing drug safety and efficacy. However, RCTs have some drawbacks which have led to the use of single-arm studies…
Optimal Bayesian hierarchical model to accelerate the development of tissue-agnostic drugs and basket trials
Liyun Jiang, Lei Nie, Fangrong Yan +1
Tissue-agnostic trials enroll patients based on their genetic biomarkers, not tumor type, in an attempt to determine if a new drug can successfully treat disease conditions based o…
A Note on Bayesian Modeling Specification of Censored Data in JAGS
Xinyue Qi, Shouhao Zhou, Martyn Plummer
Just Another Gibbs Sampling (JAGS) is a convenient tool to draw posterior samples using Markov Chain Monte Carlo for Bayesian modeling. However, the built-in function dinterval() t…
A Framework for Mediation Analysis with Multiple Exposures, Multivariate Mediators, and Non-Linear Response Models
James P. Long, Ehsan Irajizad, James D. Doecke +2
Mediation analysis seeks to identify and quantify the paths by which an exposure affects an outcome. Intermediate variables which are effected by the exposure and which effect the…
Elastic Priors to Dynamically Borrow Information from Historical Data in Clinical Trials
Liyun Jiang, Lei Nie, Ying Yuan
Use of historical data and real-world evidence holds great potential to improve the efficiency of clinical trials. One major challenge is how to effectively borrow information from…
Design of phase III trials with long-term survival outcomes based on short-term binary results
Marta Bofill Roig, Yu Shen, Guadalupe Gómez Melis
Pathologic complete response (pCR) is a common primary endpoint for a phase II trial or even accelerated approval of neoadjuvant cancer therapy. If granted, a two-arm confirmatory…
RCRnorm: An integrated system of random-coefficient hierarchical regression models for normalizing NanoString nCounter data
Gaoxiang Jia, Xinlei Wang, Qiwei Li +4
Formalin-fixed paraffin-embedded (FFPE) samples have great potential for biomarker discovery, retrospective studies and diagnosis or prognosis of diseases. Their application, howev…
Bayesian Inference of Networks Across Multiple Sample Groups and Data Types
Elin Shaddox, Christine B. Peterson, Francesco C. Stingo +5
In this paper, we develop a graphical modeling framework for the inference of networks across multiple sample groups and data types. In medical studies, this setting arises wheneve…
Estimating the Optimal Linear Combination of Biomarkers using Spherically Constrained Optimization
Priyam Das, Debsurya De, Raju Maiti +5
In the context of a binary classification problem, the optimal linear combination of continuous predictors can be estimated by maximizing an empirical estimate of the area under th…
Bayesian Modeling of Multiple Structural Connectivity Networks During the Progression of Alzheimer's Disease
Christine B. Peterson, Nathan Osborne, Francesco C. Stingo +3
Alzheimer's disease is the most common neurodegenerative disease. The aim of this study is to infer structural changes in brain connectivity resulting from disease progression usin…