Contributed Papers

Modern Developments in Bayesian Statistics

Tue, Aug 5, 8:30 AM - 10:20 AM Room CC-209A Music City Center

International Society for Bayesian Analysis (ISBA)

7 Presentations

A Framework for Simulating Populations to Quantify Uncertainty

8:35 AM - 8:50 AM

Co-authors: Christopher Grubb (Virginia Tech), Christopher Grubb (Virginia Tech), David Higdon (Virginia Tech), Leanna House (Virginia Tech)

social policy simulation models agent-based models synthetic populations population modeling uncertainty quantification

WITHDRAWN A Novel Bayesian Hierarchical Approach for the Joint Modeling of Binary and Continuous Outcomes

8:50 AM - 9:05 AM

Co-authors: Min Wang (University of Texas At San Antonio), Prince Buti

Joint modeling Bayesian hierarchical modeling MCMC methods Variable selection

Bayesian Hierarchical Penalized Spline Models in Stepped Wedge Cluster Randomized Trials

9:05 AM - 9:20 AM

Co-authors: Danni Wu (Harvard University), Hyung Park (New York University Grossman School of Medicine), Danni Wu (Harvard University), Corita Grudzen (Memorial Sloan Kettering Cancer Center), Keith Goldfeld (New York University Grossman School of Medicine)

Cluster randomized trial Bayesian hierarchical models Penalized spline Time-varying treatment effect Stepped wedge

Bayesian multinomial multilevel logistic regression with fixed- and random-effects selection

9:20 AM - 9:35 AM

Co-authors: Bertil Wegmann (Linköping University), Hector Rodriguez-Deniz (Data Science Institute, Columbia University), Bertil Wegmann (Linköping University)

Bayesian inference Multinomial logit Hierarchical modeling Gibbs sampling Polya-Gamma augmentation Spike and slab

Estimating the Number of Components in Finite Mixture Models via Variational Approximation

9:35 AM - 9:50 AM

Co-authors: Chenyang Wang, Yun Yang (University of Illinois Urbana-Champaign), Chenyang Wang

Finite mixture models Model selection Evidence lower bound Mean-field approximation Singular models

Identifying Treatment Effect Heterogeneity with Bayesian Hierarchical Adjustable Random Partition

9:50 AM - 10:05 AM

Co-authors: Xianglin Zhao, Shirin Golchi (McGill University), Xianglin Zhao

Precision Medicine Bayesian Adaptive Trials Bayesian Hierarchical Model Finite Mixture Model Reversible jump Markov Chain Monte Carlo Random Partition

Minimax Bayesian Predictive Inference with the Horseshoe Prior

10:05 AM - 10:20 AM

Co-authors: Percy Zhai (The University of Chicago), Percy Zhai (The University of Chicago), Veronika Rockova (The University of Chicago)

Horseshoe Prior Predictive Inference Sparse Normal Means Kullback-Leibler Loss Asymptotic Minimaxity