2 citations · 5 across the 7 of their papers we have counts for
7 papers
A joint model for (un)bounded longitudinal markers, competing risks, and recurrent events using patient registry data
Pedro Miranda Afonso, Dimitris Rizopoulos, Anushka K. Palipana +5
Joint models for longitudinal and survival data have become a popular framework for studying the association between repeatedly measured biomarkers and clinical events. Nevertheles…
Bayesian Shape Invariant Model for Latent Growth Curve with Time-Invariant Covariates
Mohammad Alfrad Nobel Bhuiyan, Heidi Sucharew, Rhonda Szczesniak +4
In the attention-deficit hyperactivity disorder (ADHD) study, children are prescribed different stimulant medications. The height measurements are recorded longitudinally along wit…
Mixed-Stationary Gaussian Process for Flexible Non-Stationary Modeling of Spatial Outcomes
Leo L. Duan, Xia Wang, Rhonda D. Szczesniak
Gaussian processes (GPs) are commonplace in spatial statistics. Although many non-stationary models have been developed, there is arguably a lack of flexibility compared to equippi…
Integrating Latent Classes in the Bayesian Shared Parameter Joint Model of Longitudinal and Survival Outcomes
Eleni-Rosalina Andrinopoulou, Kazem Nasserinejad, Rhonda Szczesniak +1
Cystic fibrosis is a chronic lung disease which requires frequent patient monitoring to maintain lung function over time and minimize onset of acute respiratory events known as pul…
Functional Gaussian Process Model for Bayesian Nonparametric Analysis
Leo L. Duan, Xia Wang, Rhonda D. Szczesniak
Gaussian process is a theoretically appealing model for nonparametric analysis, but its computational cumbersomeness hinders its use in large scale and the existing reduced-rank so…
Joint Hierarchical Gaussian Process Model with Application to Forecast in Medical Monitoring
Leo L. Duan, John P. Clancy, Rhonda D. Szczesniak
A novel extrapolation method is proposed for longitudinal forecasting. A hierarchical Gaussian process model is used to combine nonlinear population change and individual memory of…
BET: Bayesian Ensemble Trees for Clustering and Prediction in Heterogeneous Data
Leo L. Duan, John P. Clancy, Rhonda D. Szczesniak
We propose a novel "tree-averaging" model that utilizes the ensemble of classification and regression trees (CART). Each constituent tree is estimated with a subset of similar data…