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Legend:
CC = Walter E. Washington Convention Center   M = Marriott Marquis Washington, DC
* = applied session       ! = JSM meeting theme

Activity Details


CE_09C
Sun, 8/7/2022, 8:30 AM - 5:00 PM CC-146C
Practical Considerations for Bayesian and Frequentist Adaptive Clinical Trials — Professional Development Continuing Education Course
ASA, Section on Bayesian Statistical Science
Instructor(s): Peter Mueller, The University of Texas at Austin; Byron Jones, Novartis; Frank Bretz, Novartis
Clinical trials play a critical role in pharmaceutical drug development. New trial designs often depend on historical data, which, however, may not be accurate for the current study due to changes in study populations, patient heterogeneity, or different medical facilities. As a result, the original study design may need to be adjusted or even altered to accommodate new findings and unexpected interim results. Through carefully thought-out and planned adaptations, the right dose can be identified faster, patients can be treated more effectively, and treatment effects evaluated more efficiently. Reflecting the increasing importance and use of adaptive clinical trials, the International Council for Harmonisation (ICH) has recently tasked a working group to develop harmonized regulatory guidance for these studies in global drug development programs. This one-day short course introduces various adaptive methods for Phase I to Phase III clinical trials using both, frequentist and Bayesian methods. Accordingly, we introduce different types of adaptive designs and illustrate practical considerations with case studies. Types of adaptive designs covered in this course include dose escalation/de-escalation and dose insertion designs, adaptive dose finding studies, trials with blinded and unblinded sample size re-estimation as well as adaptive designs for confirmatory trials with treatment or population selection at interim.
 
 

4 * !
Sun, 8/7/2022, 2:00 PM - 3:50 PM CC-151B
Recent Advancements in Prior Elicitation and Computational Tools for Bayesian Design and Analysis — Invited Papers
Section on Bayesian Statistical Science, Biometrics Section, Biopharmaceutical Section
Organizer(s): Joseph G Ibrahim, University of North Carolina
Chair(s): Ethan Alt, Harvard University
2:05 PM Practical Considerations in Power Prior: Interpretation and Software Advancements
Fang Chen, SAS Institute Inc.; Frank G. Liu, Merck & Co., Inc
2:30 PM The Scale-Transformed Power Prior for Use with Historical Data from a Different Outcome Model
Joseph G Ibrahim, University of North Carolina; Brady G Nifong, University of North Carolina; Matthew A. Psioda, University of North Carolina at Chapel Hill
2:55 PM A Hierarchical Prior for Generalized Linear Models Based on Predictions for the Mean Response
Matthew A. Psioda, University of North Carolina at Chapel Hill; Joseph G Ibrahim, University of North Carolina; Ethan Alt, Harvard University
3:20 PM Flexible Conditional Borrowing Approaches for Leveraging Historical Data in the Bayesian Design of Superiority Trials
Wenlin Yuan, University of Connecticut; Ming-Hui Chen, University of Connecticut; John Zhong, REGENXBIO Inc.
3:45 PM Floor Discussion
 
 

20 * !
Sun, 8/7/2022, 2:00 PM - 3:50 PM CC-159AB
Applications of Text Analysis — Topic Contributed Papers
Text Analysis Interest Group, Government Statistics Section, Section on Bayesian Statistical Science
Organizer(s): David Banks, Duke University
Chair(s): Mark Ward, Purdue University
2:05 PM Text Mining and Music Mining
Qiuyi Wu, University of Rochester
2:25 PM Representation Learning: A Causal Perspective
Yixin Wang, University of Michigan; Michael Jordan, UC Berkeley
2:45 PM Coding Interviewer Question-Asking Behaviors in Surveys Using Recurrent Neural Networks: Do Question Characteristics Matter?
Jerry Timbrook, RTI International
3:05 PM Statistical Insights from Consumer Complaints
Ricky Rambharat, Office of the Comptroller of the Currency; Stephen Karolyi, Office of the Comptroller of the Currency
3:25 PM Discussant: David Banks, Duke University
3:45 PM Floor Discussion
 
 

27
Sun, 8/7/2022, 2:00 PM - 3:50 PM CC-140A
SPEED: Statistical Learning and Data Challenge Part 1 — Contributed Speed
Section on Statistical Learning and Data Science, Section on Bayesian Statistical Science, Section on Statistics and Data Science Education
Chair(s): Dena M Asta, The Ohio State University
2:05 PM Understanding Changes of Racial and Ethnic Representation in Homeowners and US Post-Secondary Institutions
Jhonatan Jorge Medri Cobos, University of South Florida; Tejasvi Channagiri, University of South Florida
2:10 PM Examining Relationships Between Household Conditions and Educational Outcomes at the District Level
Erin Walker Post, The University of Iowa
2:15 PM Public Transit Policies to Promote Equitable Urban Mobility
Jenny Y Huang, Duke University; Gaurav Rajesh Parikh, Duke Kunshan University; Albert Sun, Duke University
2:20 PM LinCDE: Conditional Density Estimation via Lindsey's Method
Zijun Gao, Stanford University; Trevor Hastie, Stanford University
2:25 PM Quantifying Estimation Error of Nonlinear Kalman-Type Filters
Shihong Wei, The Johns Hopkins University; James Spall, The Johns Hopkins University
2:30 PM Random Forest for Individualized Treatment Regimes in Observational Student Success Studies
Juanjuan Fan, San Diego State University; Luo Li, San Diego State University; Richard A Levine, San Diego State University
2:35 PM Stochastic Gradient Descent for Estimation and Inference in Spatial Quantile Models
Gan Luan, New Jersey Institute of Technology; Jimeng Loh, NJIT
2:40 PM Popularity Adjusted Block Models Are Generalized Random Dot Product Graphs
John Koo, Indiana University; Minh Tang, North Carolina State University; Michael Trosset, Indiana University
2:50 PM Extrapolation Control Using K-Nearest Neighbors
Kasia Dobrzycka, North Carolina State University; Jonathan Stallrich, North Carolina State University; Christopher M. Gotwalt, SAS Institute
2:55 PM A Continual Learning Framework for Adaptive Defect Classification and Inspection
Wenbo Sun, University of Michigan Transportation Research Institute; Raed Al Kontar, University of Michigan; Judy Jin, University of Michigan; Tzyy-Shuh Chang, OG Technology
3:00 PM HODOR: A Two-Stage Hold-Out Design for Online Controlled Experimentation on Networks
Nicholas Alfredo Larsen, North Carolina State University; Jonathan Stallrich, North Carolina State University; Srijan Sengupta, NCSU
3:05 PM Utilizing Open Source Resources to Teach Introductory Data Science
Tyler George, Cornell College
3:10 PM Fast Bayesian Estimation for Ranking Models
Michael Pearce, University of Washington
3:15 PM Diversity in Project-Based Learning Strategy in Undergraduate Statistics Education
Shurong Fang, John Carroll University; Lisa Dierker, Wesleyan University
3:20 PM Incorporating Cultural Context in Statistics Courses Through Presentation of Music Videos Before Class
Thomas R. Belin, UCLA Department of Biostatistics
3:25 PM Boosting Students' Programming Interest Using an R Shiny Web App Rstats in Introductory Statistics Courses
Xuemao Zhang, East Stroudsburg University
3:30 PM Student Perceptions on Reproducible Research in Introductory and Advanced Statistics Courses
Nicholas W Bussberg, Elon University
3:35 PM Changes in Undergraduate Attitudes Towards Statistics After Working as Statistical Consultants
Tracy Morris, University of Central Oklahoma; Tyler Cook, University of Central Oklahoma; Cynthia Murray, University of Central Oklahoma
3:40 PM Floor Discussion
 
 

51 !
Sun, 8/7/2022, 4:00 PM - 5:50 PM CC-207B
BFF: Innovation in Statistical Foundations — Topic Contributed Papers
Section on Bayesian Statistical Science, IMS, International Statistical Institute
Organizer(s): Jan Hannig, University of Noerth Carolina at Chapel Hill
Chair(s): Hari Iyer, National Institute of Standards & Technology
4:05 PM Fiducial Made Sexy
Thomas Lee, UC Davis
4:25 PM Conformal Predictors Constructed from Generalized Fiducial Inference
Jonathan P Williams, North Carolina State University
4:45 PM Conformal Prediction with Knowledge Transfer
Linjun Zhang, Rutgers University
5:05 PM Warrant and Severity in Statistical Inference
Ruobin Gong, Rutgers University
5:25 PM Discussant: Jan Hannig, University of Noerth Carolina at Chapel Hill
5:45 PM Floor Discussion
 
 

56 * !
Sun, 8/7/2022, 4:00 PM - 5:50 PM CC-143A
Modern Bayesian Methods for Complex Spatial Data — Topic Contributed Papers
International Society for Bayesian Analysis (ISBA), Section on Bayesian Statistical Science, Section on Statistical Computing
Organizer(s): Aritra Halder, University of Virginia; Shariq Mohammed, Boston University
Chair(s): Shariq Mohammed, Boston University
4:05 PM Curvature Processes: Directional Concavity in Gaussian Random Fields
Aritra Halder, University of Virginia
4:25 PM Beyond Gaussian Processes: Flexible Bayesian Modeling and Inference for Geostatistical Processes
Marcos Oliveira Prates, Universidade Federal de Minas Gerais; Guilherme Aparecido Santos Aguilar, Universidade Federal de Minas Gerais; Flávio Bambirra Gonçalves, Universidade Federal de Minas Gerais
4:45 PM Covariate-Dependent Spatial Ensemble Modeling for Estimating Ambient Air Pollution Concentrations
Howard Chang, Emory University
5:05 PM Spatial Factor Models for High-Dimensional Binary Data Across Large Spatial Domains: A Case Study on Breeding Birds in the United States
Jeffrey W. Doser, Michigan State University; Andrew O. Finley, Michigan State University; Sudipto Banerjee, UCLA
5:25 PM Floor Discussion
 
 

64
Sun, 8/7/2022, 4:00 PM - 5:50 PM CC-140B
Computational Advances in Bayesian Inference — Contributed Papers
Section on Bayesian Statistical Science
Chair(s): Kuan Liu, University of Toronto
4:05 PM Bayesian Parameter Inference for High-Dimensional, Nonlinear Stochastic Biological Systems Using an Approximation
Ben Swallow, University of Glasgow; David Rand, University of Warwick; Giorgos Minas, University of St Andrews
4:20 PM Bayesian Data Augmentation for Recurrent Events with Intermittent Assessment in Overlapping Intervals
Xin Liu, The Ohio State University, College of Public Health, Division of Biostatistics; Patrick M Schnell, The Ohio State University
4:35 PM Data Augmentation for Bayesian Deep Learning Presentation
Yuexi Wang, University of Chicago; Nicholas Polson, University of Chicago; Vadim Sokolov, George Mason University
4:50 PM Bounding Wasserstein Distance with Couplings
Niloy Biswas, Harvard University; Lester Mackey, Microsoft Research New England
5:05 PM Fast Big Data Spatial Process Regression Using Hierarchical Modeling
Pallavi Ray, Eli Lilly and Company; Debdeep Pati, Texas A&M University; Anirban Bhattacharya, Texas A&M University
5:20 PM A Zero-Inflated Conway--Maxwell--Poisson Regression Model with Spatially-Varying Dispersion for Spatiotemporal Data of US Vaccine Refusal
Bokgyeong Kang, The Pennsylvania State University; John Hughes, Lehigh University; Shweta Bansal, Georgetown University; Murali Haran, Pennsylvania State University
5:35 PM Floor Discussion
 
 

72
Sun, 8/7/2022, 4:00 PM - 4:45 PM CC-Hall D
SPEED: Statistical Learning and Data Challenge Part 2 — Contributed Poster Presentations
Section on Statistical Learning and Data Science, Section on Bayesian Statistical Science, Section on Statistics and Data Science Education
Chair(s): Dena M Asta, The Ohio State University
01: Understanding Changes of Racial and Ethnic Representation in Homeowners and US Post-Secondary Institutions
Jhonatan Jorge Medri Cobos, University of South Florida; Tejasvi Channagiri, University of South Florida
02: Examining Relationships Between Household Conditions and Educational Outcomes at the District Level
Erin Walker Post, The University of Iowa
03: Public Transit Policies to Promote Equitable Urban Mobility
Jenny Y Huang, Duke University; Gaurav Rajesh Parikh, Duke Kunshan University; Albert Sun, Duke University
04: Are There Home Affordability Hot Spots in the United States?
Dane Korver, NC State University; Maegan Frederick, NC State University; Fang Wu, NC State University
05: LinCDE: Conditional Density Estimation via Lindsey's Method
Zijun Gao, Stanford University; Trevor Hastie, Stanford University
06: Quantifying Estimation Error of Nonlinear Kalman-Type Filters
Shihong Wei, The Johns Hopkins University; James Spall, The Johns Hopkins University
07: Random Forest for Individualized Treatment Regimes in Observational Student Success Studies
Juanjuan Fan, San Diego State University; Luo Li, San Diego State University; Richard A Levine, San Diego State University
08: Stochastic Gradient Descent for Estimation and Inference in Spatial Quantile Models
Gan Luan, New Jersey Institute of Technology; Jimeng Loh, NJIT
09: Popularity Adjusted Block Models Are Generalized Random Dot Product Graphs
John Koo, Indiana University; Minh Tang, North Carolina State University; Michael Trosset, Indiana University
10: Extrapolation Control Using K-Nearest Neighbors
Kasia Dobrzycka, North Carolina State University; Jonathan Stallrich, North Carolina State University; Christopher M. Gotwalt, SAS Institute
11: Changes in Undergraduate Attitudes Towards Statistics After Working as Statistical Consultants
Tracy Morris, University of Central Oklahoma; Tyler Cook, University of Central Oklahoma; Cynthia Murray, University of Central Oklahoma
12: A Continual Learning Framework for Adaptive Defect Classification and Inspection
Wenbo Sun, University of Michigan Transportation Research Institute; Raed Al Kontar, University of Michigan; Judy Jin, University of Michigan; Tzyy-Shuh Chang, OG Technology
13: HODOR: A Two-Stage Hold-Out Design for Online Controlled Experimentation on Networks
Nicholas Alfredo Larsen, North Carolina State University; Jonathan Stallrich, North Carolina State University; Srijan Sengupta, NCSU
14: Utilizing Open Source Resources to Teach Introductory Data Science
Tyler George, Cornell College
15: Fast Bayesian Estimation for Ranking Models
Michael Pearce, University of Washington
16: Diversity in Project-Based Learning Strategy in Undergraduate Statistics Education
Shurong Fang, John Carroll University; Lisa Dierker, Wesleyan University
17: Incorporating Cultural Context in Statistics Courses Through Presentation of Music Videos Before Class
Thomas R. Belin, UCLA Department of Biostatistics
18: Boosting Students' Programming Interest Using an R Shiny Web App Rstats in Introductory Statistics Courses
Xuemao Zhang, East Stroudsburg University
19: Developing Data Science Skills Using Call of Duty Data
Matt Slifko, High Point University
20: Student Perceptions on Reproducible Research in Introductory and Advanced Statistics Courses
Nicholas W Bussberg, Elon University
 
 

99 *
Mon, 8/8/2022, 8:30 AM - 10:20 AM CC-154A
Applied Bayesian Methods in Sciences — Topic Contributed Papers
Korean International Statistical Society, International Society for Bayesian Analysis (ISBA), Section on Bayesian Statistical Science
Organizer(s): Seongho Song, University of Cincinnati
Chair(s): Dipak K Dey, University of Connecticut
8:35 AM Joint Modeling with Integrated Fractional Brownian Motion
Seongho Song, University of Cincinnati; Anushka Palipana, University of Cincinnati; Rhonda Szczesniak, Cincinnati Children's Hospital Medical Center; Nishant D. Gupta, University of Cincinnati
8:55 AM Computer Model Emulation and Calibration Using Complex Spatial and Temporal Data
Won Chang, University of Cincinnati
9:15 AM Bayesian Variable Selection in Generalized Linear Mixed Models Using Gaussian and Diffused-Gamma Prior with Application to Breastfeeding Study
Jiyeon Song, University of Michigan; Elizabeth Schifano, University of Connecticut; Dipak K Dey, University of Connecticut
9:35 AM Bayesian Model Calibration and Sensitivity Analysis for Oscillating Biological Experiments
Hang Joon Kim, University of Cincinnati
9:55 AM Floor Discussion
 
 

104 * !
Mon, 8/8/2022, 8:30 AM - 10:20 AM CC-144C
Advances in Bayesian Analysis of Computer Models — Topic Contributed Papers
Section on Bayesian Statistical Science, Section on Physical and Engineering Sciences
Organizer(s): Vojtech Kejzlar, Skidmore College
Chair(s): Tapabrata Maiti, Michigan State University
8:35 AM Bayesian Projected Calibration of Computer Models
Fangzheng Xie, Indiana University; Yanxun Xu, Johns Hopkins University
8:55 AM Using Gradient Descent for Gaussian Process Prediction
Matthew Plumlee, Northwestern University
9:15 AM A Fast and Calibrated Computer Model Emulator: An Empirical Bayes Approach
Vojtech Kejzlar, Skidmore College; Mookyong Son, Michigan State University; Shrijita Bhattacharya, Michigan State University; Tapabrata Maiti, Michigan State University
9:35 AM Double Sequential Calibration Strategy for Stochastic Simulation Models
Arindam Fadikar, Argonne National Laboratory
9:55 AM Theory of Variational Bayes Computer Models
Shrijita Bhattacharya, Michigan State University; Mookyong Son, Michigan State University; Vojtech Kejzlar, Skidmore College; Tapabrata Maiti, Michigan State University
10:15 AM Floor Discussion
 
 

111
Mon, 8/8/2022, 8:30 AM - 10:20 AM CC-144A
Application and Development of Statistical Methods for Spatio-Temporal Data — Contributed Papers
Section on Bayesian Statistical Science
Chair(s): Yunjiang Ge, University of Maryland College Park
8:35 AM Bayesian Functional Principal Components Analysis Using Relaxed Mutually Orthogonal Processes
James Matuk, Duke University; Amy Herring, Duke University; David Dunson, Duke University
8:50 AM Bayesian Approach to the Mixture of Gaussian Random Fields and Its Application to an fMRI Study
Mozhdeh Forghaniarani, James Madison University; Khalil Shafie, University of Northern Colorado
9:05 AM Spatio-Temporal Log-Gaussian Cox Point Processes via Flexible Gaussian Random Fields
Shuwan Wang, University of Missouri-Columbia; Athanasios Micheas, University of Missouri-Columbia; Christopher K. Wikle, University of Missouri
9:20 AM Using Dirichlet Processes and Machine Learning to Estimate Crash Risk on Roadways
Benjamin K. Dahl, Brigham Young University; Matthew Heaton, BYU; Richard Warr, Brigham Young University; Philip White, BYU; Grant G. Schultz, Brigham Young University; Caleb Dayley, Brigham Young University
9:35 AM Covariate-Guided Bayesian Mixture of Spline Experts for the Analysis of Multivariate Time Series
Haoyi Fu, University of Pittsburgh; Ori Rosen, University of Texas at El Paso; Lu Tang, University of Pittsburgh; Alison Hipwell, University of Pittsburgh; Theodore Huppert, University of Pittsburgh; Kate Keenan, University of Chicago; Robert T Krafty, Emory University
9:50 AM Bayesian Analysis for Spatial Interval-Valued Data
Austin Workman, Baylor University; Joon Jin Song, Baylor Univeristy
10:05 AM Floor Discussion
 
 

126 * !
Mon, 8/8/2022, 10:30 AM - 12:20 PM CC-101
Topics at the Frontier of Statistical Computing and Machine Learning — Invited Papers
Section on Bayesian Statistical Science, Section on Statistical Computing, Section on Statistical Learning and Data Science
Organizer(s): Robert Kohn, University of New South Wales
Chair(s): Hung Dao, University of New South Wales
10:35 AM Flexible Variational Bayes Based on a Copula of a Mixture of Normals
Robert Kohn, University of New South Wales; David Gunawan, School of Mathematics and Applied Statistics; David Nott, University of Singapore
11:05 AM Variational Bayes on Manifolds
Minh-Ngoc Tran, University of Sydney; Dang Nguyen, University of Alabama; Duy Nguyen, Marist College
11:35 AM Sparse Hamiltonian Flows (Or Bayesian Coresets Without All the Fuss)
Trevor Campbell, UBC; Naitong Chen, University of British Columbia; Zuheng Xu, University of British Columbia - Vancouver, BC
12:05 PM Floor Discussion
 
 

143
Mon, 8/8/2022, 10:30 AM - 12:20 PM CC-140A
SPEED: Bayesian Methods and Social Statistics Part 1 — Contributed Speed
Section on Bayesian Statistical Science, Social Statistics Section, Section on Statistics in Marketing, Text Analysis Interest Group
Chair(s): Jorge Luis Romeu, Syracuse University
10:35 AM Spatial Structure and Labor Market Integration Projections in Germany
Monika Obersneider, University of Duisburg-Essen; Petra Stein, University of Duisburg-Essen
10:40 AM Jury Perception of Bullet Matching Algorithms and Demonstrative Evidence
Rachel Rogers, University of Nebraska-Lincoln; Susan VanderPlas, University of Nebraska - Lincoln
10:45 AM Parameter-Expanded Data Augmentations for Analyzing Mixed Ordinal and Continuous Data with Missing Values
Xiao Zhang, Michigan Technological University
10:50 AM Bayesian Nonparametric Inference on Restricted Mean Survival Time with Adjustments for Covariates
Ruizhe Chen, University of Illinois Chicago; Sanjib Basu, Biostatistics, University of Illinois Chicago; Qian Shi, Mayo Clinic
10:55 AM Causal Inference for Health Effects of Time-Varying Correlated Environmental Mixtures
Zilan Chai, Columbia University; Linda Valeri, Columbia University; Ana Navas-Acien, Columbia University; Brent Coull, Harvard University
11:00 AM Zero-Inflated Hierarchical Generalized Dirichlet Multinomial Bayesian Regression Model with Cyclic Splines for Analysis of TDP-43 on the ALS-FTD Spectrum
Patrick Gravelle, Brown University; Roee Gutman, Brown University
11:05 AM Approaches to Cost-Constrained Bayesian Model Selection
Erica May Porter, Virginia Tech; Christopher Franck, Virginia Tech; Stephen Adams, Virginia Tech Hume Center
11:10 AM Likelihood Ratios for Categorical Evidence with Applications to Digital Forensics
Rachel Longjohn, University of California Irvine; Padhraic Smyth, University of California Irvine
11:15 AM A Bayesian Kernel Machine Regression Approach to Assessing the Effect of Heavy Metal Mixtures in on the Risk of Heart Attack
Kazi Tanvir Hasan, Florida International University; Boubakari Ibrahimou, Florida International University; Shelbie Burchfield, Florida International University
11:20 AM Automated Detection of Edge Clusters via an Overfitted Mixture Prior
Hanh Pham, University of Iowa; Daniel Sewell, University of Iowa
11:35 AM Optional Randomized Response Technique for Estimating Proportions of Two Sensitive Characteristics and Their Overlap
Kavya Pushadapu, Texas A&M University-Kingsville; Sarjinder Singh, Texas A&M University-Kingsville
11:40 AM Bias Correction for Sampled Genetic Network Data
Gabrielle Lemire, Montana State University; Nicole Carnegie, Montana State University; Ravi Goyal, University of California San Diego; Breschine Cummins, Montana State University
11:45 AM Associations Between Digital Divide Indicators and Employment Retention Among Workers with and Without Disabilities
Amy Fong, Department of Labor - Office of Disability Employment Policy
11:50 AM Nonlinear Spatial Data Analysis for Induced Terminations of Pregnancy (ITOP) Incidents at Texas
YOONSUNG JUNG, Prairie View A&M University; Duchwan Ryu, Northern Illinois University
11:55 AM Modeling and Understanding Social Polarization in News Media
Shane Dakota Bookhultz, Virginia Tech; David Edwards, Virgnia Tech; Scotland Leman, Virginia Tech; Shyam Ranganathan, Clemson University; James Hawdon, Virginia Tech
12:00 PM Floor Discussion
 
 

189
Mon, 8/8/2022, 2:00 PM - 3:50 PM CC-159AB
SBSS Student Paper Competition I — Topic Contributed Papers
Section on Bayesian Statistical Science, International Society for Bayesian Analysis (ISBA)
Organizer(s): Veronica J Berrocal, University of California
Chair(s): Veronica J Berrocal, University of California
2:05 PM Warped Dynamic Linear Models for Time Series of Counts
Brian King, Rice University; Daniel Kowal, Rice University
2:25 PM An Alternative Metric for Evaluating the Potential Patient Benefit of Response-Adaptive Randomization Procedures
Jennifer Lauren Proper, University of Minnesota Twin Cities; Thomas Murray , University of Minnesota
2:45 PM The Computational Asymptotics of Gaussian Variational Inference and the Laplace Approximation
Zuheng Xu, University of British Columbia - Vancouver, BC; Trevor Campbell, UBC
3:05 PM A Variational Bayesian Approach to Identifying Whole-Brain Directional Networks with fMRI Data
Yaotian Wang, University of Pittsburgh; Guofen Yan, University of Virginia; Xiaofeng Wang, Cleveland Clinic Lerner College of Medicine of Case Western Reserve University; Tingting Zhang, University of Pittsburgh
3:25 PM Density Regression with Bayesian Additive Regression Trees
Vittorio Orlandi, Duke University; Jared S Murray, The University of Texas McCombs School of Business; Antonio R. Linero, University of Texas at Austin; Alex Volfovsky, Duke University
3:45 PM Floor Discussion
 
 

191 !
Mon, 8/8/2022, 2:00 PM - 3:50 PM CC-158AB
Misspecification and Robustness: Novel Methods and Innovative Insights — Topic Contributed Papers
International Society for Bayesian Analysis (ISBA), Section on Bayesian Statistical Science, IMS
Organizer(s): Jeffrey Miller, Harvard TH Chan School of Public Health
Chair(s): Diana Cai, Princeton University
2:05 PM Bayesian Data Selection
Eli Nathan Weinstein, Columbia University; Jeffrey Miller, Harvard TH Chan School of Public Health
2:25 PM Robust Inference Using Posterior Bootstrap
Emilia Pompe, University of Oxford
2:45 PM Fast Approximate BayesBag Model Selection via Taylor Expansions
Neil Archibald Spencer, Harvard University; Jeffrey Miller, Harvard TH Chan School of Public Health
3:05 PM On the Robustness to Misspecification of Alpha-Posteriors and Their Variational Approximations
Marco Avella Medina, Columbia University; Cynthia Rush, Columbia University; Jose Luis Montiel Olea, Columbia University; Amilcar Velez, Northwestern University
3:25 PM Truth-Agnostic Diagnostics for Calibration Under Misspecification
Jeffrey Miller, Harvard TH Chan School of Public Health; Jonathan H Huggins, Boston University
3:45 PM Floor Discussion
 
 

202
Mon, 8/8/2022, 2:00 PM - 3:50 PM CC-156
Meta-Analysis, Mediation, and Causal Inference from a Bayesian Perspective — Contributed Papers
Section on Bayesian Statistical Science
Chair(s): Binbing Yu, AstraZeneca
2:05 PM Bayesian Dynamic Borrowing of Historical Information with Applications to the Analysis of Large-Scale Assessments
David Kaplan, University of Wisconsin - Madison
2:20 PM Empirical Bayesian Estimation of Malware Detection Without Knowing Ground Truth
Keying Ye, University of Texas at San Antonio; Min Wang, The University of Texas at San Antonio; Ambassador Negash, University of Texas at San Antonio; Zifei Han, University of International Business and Economics
2:35 PM Bayesian Hierarchical Models for Multivariate Meta-Analysis of Diagnostic Tests in the Absence of a Gold Standard with an Application to SARS-CoV-2 Infection Diagnosis
Zheng Wang, University of Minnesota; Haitao Chu, Pfizer Inc.; Thomas Murray , University of Minnesota ; Mengli Xiao, University of Minnesota Twin Cities; Lifeng Lin, Florida State University; Demissie Alemayehu, Pfizer Inc.
2:50 PM A Bayesian Meta-Analysis Approach for Penetrance Estimation and Its Application to the Estimation of Breast Cancer Risk for ATM Carriers
Thanthirige Lakshika Maduwanthi Ruberu, University of Texas at Dallas; Danielle Braun, Harvard T.H. Chan School of Public Health; Giovanni Parmigiani, Harvard T.H. Chan School of Public Health; Swati Biswas, University of Texas at Dallas
3:05 PM Bayesian Mediation Analysis Methods to Explore Racial/Ethnic Disparities in Anxiety Among Cancer Survivors
Qingzhao Yu, Louisiana State University Health Science Center; Bin Li, Louisiana State University
3:20 PM A Bayesian Comparative Effectiveness Trial in Action: Executing a Multi-Site Study with Response-Adaptive Randomization Presentation
Alexandra Brown, University of Kansas Medical Center; Byron Gajewski, University of Kansas Medical Center; Dinesh Pal Mudaranthakam, University of Kansas Medical Center; Mamatha Pasnoor, University of Kansas Medical Center; Mazen Dimachkie, University of Kansas Medical Center; Omar Jawdat, University of Kansas Medical Center; Laura Herbelin, University of Kansas Medical Center; Richard Barohn, University of Missouri Health Care
3:35 PM Uncertainty Calibration and Exemplar Identification for Heterogeneous Treatment Effects with Individualized Bayesian Causal Forests
Jennifer Starling, Mathematica Policy Research; Lauren Vollmer, Mathematica Policy Research; Erin Lipman, University of Washington; Peter Mariani, Mathematica Policy Research; Daniel Thal, Mathematica Policy Research; Irina Degtiar, Mathematica Policy Research; Mariel McKenzie Finucane, Mathematica
 
 

208
Mon, 8/8/2022, 2:00 PM - 2:45 PM CC-Hall D
SPEED: Bayesian Methods and Social Statistics Part 2 — Contributed Poster Presentations
Section on Bayesian Statistical Science, Social Statistics Section, Section on Statistics in Marketing
Chair(s): Jorge Luis Romeu, Syracuse University
01: Spatial Structure and Labor Market Integration Projections in Germany
Monika Obersneider, University of Duisburg-Essen; Petra Stein, University of Duisburg-Essen
02: Jury Perception of Bullet Matching Algorithms and Demonstrative Evidence
Rachel Rogers, University of Nebraska-Lincoln; Susan VanderPlas, University of Nebraska - Lincoln
03: Parameter-Expanded Data Augmentations for Analyzing Mixed Ordinal and Continuous Data with Missing Values
Xiao Zhang, Michigan Technological University
04: Bayesian Nonparametric Inference on Restricted Mean Survival Time with Adjustments for Covariates
Ruizhe Chen, University of Illinois Chicago; Sanjib Basu, Biostatistics, University of Illinois Chicago; Qian Shi, Mayo Clinic
05: Causal Inference for Health Effects of Time-Varying Correlated Environmental Mixtures
Zilan Chai, Columbia University; Linda Valeri, Columbia University; Ana Navas-Acien, Columbia University; Brent Coull, Harvard University
06: Zero-Inflated Hierarchical Generalized Dirichlet Multinomial Bayesian Regression Model with Cyclic Splines for Analysis of TDP-43 on the ALS-FTD Spectrum
Patrick Gravelle, Brown University; Roee Gutman, Brown University
07: Approaches to Cost-Constrained Bayesian Model Selection
Erica May Porter, Virginia Tech; Christopher Franck, Virginia Tech; Stephen Adams, Virginia Tech Hume Center
08: Likelihood Ratios for Categorical Evidence with Applications to Digital Forensics
Rachel Longjohn, University of California Irvine; Padhraic Smyth, University of California Irvine
09: A Bayesian Kernel Machine Regression Approach to Assessing the Effect of Heavy Metal Mixtures in on the Risk of Heart Attack
Kazi Tanvir Hasan, Florida International University; Boubakari Ibrahimou, Florida International University; Shelbie Burchfield, Florida International University
10: Automated Detection of Edge Clusters via an Overfitted Mixture Prior
Hanh Pham, University of Iowa; Daniel Sewell, University of Iowa
11: A Bayesian Hierarchical Time Series Model for Estimating Sex Ratios in Youth Mortality
Fengqing Chao, King Abdullah University of Science and Technology; Bruno Masquelier, Universite catholique de Louvain; Haavard Rue, King Abdullah University of Science and Technology; Hernando Ombao, King Abdullah University of Science and Technology; Leontine Alkema, University of Massachusetts, Amherst
12: Optional Randomized Response Technique for Estimating Proportions of Two Sensitive Characteristics and Their Overlap
Kavya Pushadapu, Texas A&M University-Kingsville; Sarjinder Singh, Texas A&M University-Kingsville
13: Bias Correction for Sampled Genetic Network Data
Gabrielle Lemire, Montana State University; Nicole Carnegie, Montana State University; Ravi Goyal, University of California San Diego; Breschine Cummins, Montana State University
14: Associations Between Digital Divide Indicators and Employment Retention Among Workers with and Without Disabilities
Amy Fong, Department of Labor - Office of Disability Employment Policy
15: Nonlinear Spatial Data Analysis for Induced Terminations of Pregnancy (ITOP) Incidents at Texas
YOONSUNG JUNG, Prairie View A&M University; Duchwan Ryu, Northern Illinois University
16: Modeling and Understanding Social Polarization in News Media
Shane Dakota Bookhultz, Virginia Tech; David Edwards, Virgnia Tech; Scotland Leman, Virginia Tech; Shyam Ranganathan, Clemson University; James Hawdon, Virginia Tech
 
 

223836
Mon, 8/8/2022, 6:00 PM - 7:00 PM CC-Ballroom A
Section on Bayesian Statistical Science Mixer and Awards — Other Cmte/Business
Section on Bayesian Statistical Science
Chair(s): Amy Herring, Duke University
 
 

238 *
Tue, 8/9/2022, 8:30 AM - 10:20 AM CC-204B
Advances in Spatial and Temporal Models for Complex Environmental Systems — Topic Contributed Papers
Section on Bayesian Statistical Science, Section on Statistics and the Environment, International Society for Bayesian Analysis (ISBA)
Organizer(s): Ephraim M Hanks, The Pennsylvania State University
Chair(s): Veronica J Berrocal, University of California
8:35 AM Realistic and Fast Modeling of Spatial Extremes Over Large Geographical Domains
Arnab Hazra, Indian Institute of Technology Kanpur; Raphael Huser, King Abdullah University of Science and Technology (KAUST); David Bolin, King Abdullah University of Science and Technology (KAUST)
8:55 AM Modeling First Arrival of Migratory Birds Using a Hierarchical Max-Infinitely Divisible Process
Benjamin Shaby, Colorado State University; Dhanushi Wijeyakulasuriya, Microsoft Corp.; Ephraim M Hanks, The Pennsylvania State University
9:15 AM Joint Modeling of Individual Telemetry and Species Distribution Data to Understand Migratory Behavior of Golden Eagles
Ephraim M Hanks, The Pennsylvania State University
9:35 AM Floor Discussion
 
 

245
Tue, 8/9/2022, 8:30 AM - 10:20 AM CC-204C
Bayesian Models for Clustering and Latent Allocation — Contributed Papers
Section on Bayesian Statistical Science
Chair(s): Satwik Acharyya, University of Michigan
8:35 AM Bayesian Regression Modeling of 0-1 Data Having Boundary Values
Eugene D Hahn, Salisbury University
8:50 AM Bayesian Hierarchical Latent Class Models for Grouped Responses
Mengbing Li, University of Michigan; Zhenke Wu, University of Michigan, Ann Arbor; Briana Joy Kennedy Stephenson, Harvard T.H. Chan School of Public Health
9:05 AM Supervised Bayesian Nonparametric Clustering Techniques for Survey Data
Stephanie M. Wu, Harvard T.H. Chan School of Public Health; Briana Joy Kennedy Stephenson, Harvard T.H. Chan School of Public Health
9:20 AM Bayesian Modeling of Co-Occurrence Microbial Interaction Networks
Tejasv Bedi, University of Texas at Dallas; Michael Neugent, University of Texas at Dallas; Xiaowei Zhan, The University of Texas Southwestern Medical Center; Nicole De Nisco, University of Texas at Dallas; Qiwei Li, The University of Texas at Dallas
9:35 AM Search Algorithms and Loss Functions for Bayesian Feature Allocation Models
Robert Jacob Andros, Brigham Young University; David B. Dahl, Brigham Young University; Devin Johnson, Duke University
9:50 AM Graph Product Partition Models
Changwoo J Lee, Texas A&M University; Huiyan Sang, Texas A&M University
10:05 AM Adversarial Hidden Markov Models with Batch Data
Tahir Ekin, Texas State University; William Nick Caballero, The United States Air Force Academy; Roi Naveiro, ICMAT-CSIC; David Rios Insua, ICMAT-CSIC
 
 

259 * !
Tue, 8/9/2022, 10:30 AM - 12:20 PM CC-143B
Modern Statistical Methods for Structured Discovery in Large Biomedical Data — Invited Papers
ENAR, Biometrics Section, Section on Bayesian Statistical Science
Organizer(s): Veera Baladandayuthapani, University of Michigan
Chair(s): Veera Baladandayuthapani, University of Michigan
10:35 AM Identifying Unobserved Mediators of High-Dimensional Phenotypes Using Empirical Bayes Matrix Decomposition
Jean Morrison, University of Michigan; Jason Willwerscheid, University of Chicago; Matthew Stephens, University of Chicago; Xin He, University of Chicago
11:00 AM Bayesian Cross-Study Factor Regression Approach
Roberta De Vito, Brown University
11:25 AM Bayesian Sparse Modeling to Identify High-Risk Subgroups
Christine B. Peterson, University of Texas MD Anderson Cancer Center
11:50 AM Bayesian Causal Discovery for Purely Observational Genomic Data
Yang Ni, Texas A&M University
12:15 PM Floor Discussion
 
 

260 !
Tue, 8/9/2022, 10:30 AM - 12:20 PM CC-144C
Science-Integrated Statistical Learning — Invited Papers
Section on Physical and Engineering Sciences, Section on Statistical Learning and Data Science, Section on Bayesian Statistical Science
Organizer(s): Simon Mak, Duke University
Chair(s): Robert Gramacy, Virginia Tech
10:35 AM Multi-Stage, Multi-Fidelity Gaussian Process Modeling, with Applications to Emulation of Heavy-Ion Collisions
Simon Mak, Duke University
11:05 AM When Epidemic Models Meet Statistics: Understanding the Impact of Weather and Government Interventions on COVID-19 Outbreak
Chih-Li Sung, Michigan State University
11:35 AM APIK: Active Physics-Informed Kriging Model with Partial Differential Equations
C. F. Jeff Wu, Georgia Inst of Tech
12:05 PM Floor Discussion
 
 

268
Tue, 8/9/2022, 10:30 AM - 12:20 PM CC-201
SBSS Student Paper Competition II — Topic Contributed Papers
Section on Bayesian Statistical Science, International Society for Bayesian Analysis (ISBA)
Organizer(s): Veronica J Berrocal, University of California
Chair(s): Huiyan Sang, Texas A&M University
10:35 AM Structured Mixture of Continuation-Ratio Logits Models for Ordinal Regression
Jizhou Kang, University of California, Santa Cruz; Athanasios Kottas, University of California, Santa Cruz
10:55 AM Robust Generalised Bayesian Inference for Intractable Likelihoods
Takuo Matsubara, Newcastle University; Jeremias Knoblauch, University College London; François-Xavier Briol, University College London; Chris Oates, Newcastle University
11:15 AM Vector-Valued Control Variates
Zhuo Sun, University College London; Alessandro Barp, University of Cambridge; François-Xavier Briol, University College London
11:35 AM Bayesian Image Mediation Analysis Presentation
Yuliang Xu, University of Michigan; Jian Kang, University of Michigan
11:55 AM Two-Sample Bayesian Causal Directed Acyclic Graphs for Observational Zero-Inflated Count Data
Junsouk Choi, Texas A&M University; Yang Ni, Texas A&M University; Robert S. Chapkin, Texas A&M University
12:15 PM Floor Discussion
 
 

Register 298
Tue, 8/9/2022, 12:30 PM - 1:50 PM CC-Ballroom Level South Prefunction
Section on Bayesian Statistical Science P.M. Roundtable Discussion (Added Fee — Roundtables PM Roundtable Discussion
Section on Bayesian Statistical Science
TL10: Bayesian Causal Inference: Basics, Challenges, and Opportunities
Fan Li, Duke University
 
 

308 * !
Tue, 8/9/2022, 2:00 PM - 3:50 PM CC-150A
Highlights in Bayesian Analysis: Innovations in Bayesian Learning — Invited Papers
Section on Bayesian Statistical Science, International Society for Bayesian Analysis (ISBA), Section on Statistical Learning and Data Science
Organizer(s): Michele Guindani, University of California, Irvine
Chair(s): Veronica J Berrocal, University of California
2:05 PM Informative Bayesian Neural Network Priors for Weak Signals
Tianyu Cui, Aalto University; Aki Havulinna, Finnish Institute for Health and Welfare (THL); Pekka Marttinen, Aalto University; Samuel Kaski, Aalto University and University of Manchester
2:30 PM Fast and Accurate Estimation of Non-Nested Binomial Hierarchical Models Using Variational Inference
Max Goplerud, University of Pittsburgh
2:55 PM Bayesian Survival Tree Ensembles with Submodel Shrinkage
Antonio R. Linero, University of Texas at Austin; Piyali Basak, Merck Pharmaceuticals; Yinpu Li, Florida State University; Debajyoti Sinha, Florida State University
3:20 PM Bayesian Hierarchical Stacking: All Models Are Wrong, but Some Are Somewhat Useful
Yuling Yao, Flatiron Institute; Gregor Pirš, University of Ljubljana; Aki Vehtari, Aalto University; Andrew Gelman, Columbia University
3:45 PM Floor Discussion
 
 

327 * !
Tue, 8/9/2022, 2:00 PM - 3:50 PM CC-143C
On Surrogate Modeling of Emerging Issues in Physical and Engineering Simulators — Topic Contributed Papers
Section on Physical and Engineering Sciences, ENAR, Section on Bayesian Statistical Science
Organizer(s): Bledar Alex Konomi, University of Cincinnati
Chair(s): Emily L Kang, University of Cincinnati
2:05 PM A Nonstationary Soft Partitioned Gaussian Process Model via Random Spanning Trees
Zhao Tang Luo, Texas A&M University; Huiyan Sang, Texas A&M University; Bani Mallick, Texas A&M University
2:25 PM Multifidelity Karhunen-Loeve Expansion Surrogate Models for Uncertainty Propagation
Xun Huan, University of Michigan; Aniket Jivani, University of Michigan; Cosmin Safta, Sandia National Laboratories
2:45 PM Dimension Reduction for Gaussian Process Models via Convex Combination of Kernels
Lulu Kang, Illinois Institute of Technology
3:05 PM B-DeepONet: An Enhanced Bayesian DeepONet for Solving Noisy Parametric PDEs Using Accelerated Replica Exchange SGLD
Guang Lin, Purdue University; Christian Moya, Purdue University; Zecheng Zhang, Purdue University
3:25 PM Emulating the Magnitude and Location of the Stormwise Maximum Surge Level
Whitney Huang, Clemson University; Taylor Asher, University of North Carolina at Chapel Hill
3:45 PM Floor Discussion
 
 

328 * !
Tue, 8/9/2022, 2:00 PM - 3:50 PM CC-151A
Recent Development in Bayesian Dynamic Borrowing with Application to Clinical Trials — Topic Contributed Panel
Biopharmaceutical Section, Section on Bayesian Statistical Science, ENAR
Organizer(s): Lei Nie, U. S. FDA
Chair(s): Ming-Hui Chen, University of Connecticut
2:05 PM Recent Development in Bayesian Dynamic Borrowing with Application to Clinical Trials
Panelists: Ying Yuan , the University of Texas MD Anderson Cancer Center
Margaret Gamalo , Pfizer Inc.
Satrajit Roychoudhury, Pfizer Inc
Hengrui Sun, FDA
Ales Kotalik, AstraZeneca
3:40 PM Floor Discussion
 
 

343
Tue, 8/9/2022, 2:00 PM - 3:50 PM CC-Hall D
Contributed Poster Presentations: Section on Bayesian Statistical Science — Contributed Poster Presentations
Section on Bayesian Statistical Science
Chair(s): Gyuhyeong Goh, Kansas State University
14: Monte Carlo Markov Chain (MCMC) Approach to Estimate Parameters of Burr Type III Distribution
Woosuk Kim, Slippery Rock University; Elijah Adam McClymonds, Slippery Rock University; Aran Bybee, Slippery Rock University; Alyssa Kasmierski, Slippery Rock University
15: Individual Level Variance as a Predictor of Health Outcomes
Irena Chen, University of Michigan; Zhenke Wu, University of Michigan, Ann Arbor; Michael Elliott, University of Michigan; Sioban D Harlow, University of Michigan; Carrie A Karvonen-Gutierrez, University of Michigan; Michelle M Hood, University of Michigan
16: A Comparison of Bayesian Accelerated Life Testing Models in the Presence of Dual Stresses
Neill Smit, North-West University; Lizanne Raubenheimer, Rhodes University
17: A Bayesian Approach Towards Probability Calibration
Christopher Franck, Virginia Tech; Adeline Guthrie, Virgina Tech
18: A Flexible Bayesian Regression Approach for Modeling Interval Data
Shubhajit Sen, North Carolina State University; Kiranmoy Das, Indian Statistical Institute
19: Bayesian Predictive Modeling from Multi-Source Multiway Data
Jonathan Kim, University of Minnesota; Eric F Lock, University of Minnesota
20: Bayesian Optimality and Intervals for Stein-Type Estimates
Lingbo Ye, University of Washington, Seattle; Ken Rice, University of Washington, Seattle
 
 

374 * !
Wed, 8/10/2022, 8:30 AM - 10:20 AM CC-201
Bayesian Clinical Trial Designs with Heterogeneous Patient Subgroups — Topic Contributed Papers
Biopharmaceutical Section, International Chinese Statistical Association, Section on Bayesian Statistical Science
Organizer(s): Kentaro Takeda, Astellas Pharma Global Development, Inc.
Chair(s): Kentaro Takeda, Astellas Pharma Global Development, Inc.
8:35 AM Dose Finding with Heterogeneous Patient Subgroups
ANASTASIA IVANOVA, UNC at Chapel Hill; Pooja Saha, Center for Biostatistics in AIDS Research, Department of Biostatistics, Harvard T.H. Chan
8:55 AM Group-Sequential Enrichment Designs Based on Adaptive Regression of Response and Survival Time on High-Dimensional Covariates
Yeonhee Park, University of Wisconsin-Madison; Suyu Liu, The University of Texas MD Anderson Cancer Center; Peter Thall, The University of Texas MD Anderson Cancer Center; Ying Yuan , the University of Texas MD Anderson Cancer Center
9:15 AM BAGS: A Bayesian Adaptive Group Sequential Trial Design with Subgroup-Specific Survival Comparisons
Ruitao Lin, MD Anderson; Peter Thall, The University of Texas MD Anderson Cancer Center; Ying Yuan , the University of Texas MD Anderson Cancer Center
9:35 AM Bayesian Divide-and-Conquer Propensity Score–Based Approaches for Leveraging Real-World Data in Randomized Control Trials
Eric Baron, University of Connecticut; Jian Zhu, Servier Pharmaceuticals; Sammi Tang, Servier Pharmaceuticals; Ming-Hui Chen, University of Connecticut
9:55 AM Incorporating Historical Information for Randomized Clinical Trials: Dynamic Borrowing with Bias Control
Masataka Taguri, Yokohama City University
10:15 AM Floor Discussion
 
 

380
Wed, 8/10/2022, 8:30 AM - 10:20 AM CC-158AB
Advances in Bayesian Extreme Value Analysis — Topic Contributed Papers
Section on Bayesian Statistical Science, Section on Statistics and the Environment, Section on Risk Analysis
Organizer(s): Benjamin Shaby, Colorado State University
Chair(s): Benjamin Shaby, Colorado State University
8:35 AM Approximating Likelihoods for Extreme Value Analysis with Deep Learning
Reetam Majumder, North Carolina State University; Brian James Reich, North Carolina State University; Benjamin Shaby, Colorado State University
8:55 AM Spatial Scale-Aware Tail Dependence Modeling for High-Dimensional Spatial Extremes
Likun Zhang, Lawrence Berkeley National Laboratory; Mark Risser, Lawrence Berkeley National Laboratory; Benjamin Shaby, Colorado State University
9:15 AM Spatiotemporal Wildfire Modeling Through Point Processes with Moderate and Extreme Marks
Jonathan Koh, University of Bern; François Pimont, INRAe; Jean-Luc Dupuy, INRAe; Thomas Opitz, INRAe
9:35 AM A Flexible Bayesian Hierarchical Modeling Framework for Spatially Dependent Peaks-Over-Threshold Data Presentation
Rishikesh Yadav, King Abdullah University of Science and Technology; Raphael Huser, King Abdullah University of Science and Technology (KAUST); Thomas Opitz, INRAe
9:55 AM Interpolation of Precipitation Extremes on a Large Domain Toward IDF Curve Construction at Unmonitored Locations
Jonathan Jalbert, Polytechnique Montréal; Christian Genest, McGill University; Luc Perreault, Hydro-Québec; Paul Mathivon, Polytechnique Montréal
10:15 AM Floor Discussion
 
 

392
Wed, 8/10/2022, 8:30 AM - 10:20 AM CC-156
Bayesian Analysis of Complex, Structured Health and Social Data — Contributed Papers
Section on Bayesian Statistical Science
Chair(s): Dexter Cahoy, University of Houston-Downtown
8:35 AM Variational Bayes Model-X Knockoffs
Kumaresh Dhara, Food and Drug Administration; Michael Daniels, University of Florida
8:50 AM Air Pollution Mixtures and Birth Outcome Morbidities
Boubakari Ibrahimou, Florida International University
9:05 AM Bayesian Inference for Continuous-Time Transmission Processes of Infectious Diseases in Close Contact Groups
Hasibul Hasan, University of Florida; Yang Yang, University of Florida; Eben Kenah, The Ohio State University
9:20 AM Bayesian Analysis of Interrater and Intrarater Reliability with Multilevel Data
Nour Hawila, Penn State University - College of Medicine; Arthur Berg, Penn State University - College of Medicine
9:35 AM Data Journalism, Statistical Methodology, and the Academy Awards: A Case Study
Christopher Franck, Virginia Tech; Christopher Wilson, TIME.com
9:50 AM Bayesian Modeling of Effective and Functional Brain Connectivity Using Hierarchical Vector Autoregressions
Bertil Wegmann, Dept of Computer and Information Science, Linköping University
10:05 AM Analyzing Dental Fluorosis Data Using a Novel Bayesian Model for Clustered Longitudinal Outcomes with an Inflated Category
Tong Kang, Bristol Myers Squibb; Jeremy Gaskins, University of Louisville; Steven Levy, University of Iowa; Somnath Datta, University of Florida
 
 

416 * !
Wed, 8/10/2022, 10:30 AM - 12:20 PM CC-102A
Open Problems in Astrostatistics — Topic Contributed Papers
Section on Physical and Engineering Sciences, Astrostatistics Special Interest Group, Section on Bayesian Statistical Science
Organizer(s): Yang Chen, University of Michigan
Chair(s): Yang Chen, University of Michigan
10:35 AM Calibrated Uncertainty Quantification with Application to Galaxy Photometric Redshifts
Ann Lee, Carnegie Mellon University
10:55 AM Topics for Statistical Advances for Use in Astronomy
Herman Marshall, MIT
11:15 AM Exploring the Quantification of Uncertainty in the Analysis of Multi-Dimensional High-Energy Astronomical Data Sets
Aneta Siemiginowska, Center for Astrophysics | Harvard & Smithsonian
11:35 AM Discussant: David van Dyk, Imperial College London
11:55 AM Discussant: Vinay Kashyap, Center for Astrophysics | Harvard & Smithsonian
12:15 PM Floor Discussion
 
 

417 !
Wed, 8/10/2022, 10:30 AM - 12:20 PM CC-204A
Statistical Methods for Discovering Latent Structures in High-Dimensional and Complex Data — Topic Contributed Papers
Section on Bayesian Statistical Science, International Society for Bayesian Analysis (ISBA), Section on Statistical Learning and Data Science
Organizer(s): Zehang Richard Li, UCSC
Chair(s): Zhenke Wu, University of Michigan, Ann Arbor
10:35 AM Bayesian Pyramids: Identifiable Multilayer Discrete Latent Structure Models for Discrete Data
Yuqi Gu, Columbia University; David Dunson, Duke University
10:55 AM Statistical Neuroscience in the Single Trial Limit
Scott Linderman, Stanford University
11:15 AM Latent Class Models for Prevalence Estimation of Emerging Diseases Using Verbal Autopsy Data
Zehang Richard Li, UCSC
11:35 AM Exploration of Latent Structure in Test Review and Revision Log Data
Susu Zhang, University of Illinois at Urbana-Champaign; Anqi Li, University of Illinois at Urbana-Champaign; Shiyu Wang, University of Georgia
11:55 AM Discussant: Elena Erosheva, University of Washington
12:15 PM Floor Discussion
 
 

424
Wed, 8/10/2022, 10:30 AM - 12:20 PM CC-204C
Priors and Model Specifications for Variable and Feature Selection — Contributed Papers
Section on Bayesian Statistical Science
Chair(s): Anupreet Porwal, University of Washington
10:35 AM Extending the Spike-and-Slab Lasso for Generalized Linear Models to Accommodate Multinomial Outcomes
Justin M Leach, University of Alabama at Birmingham; Nengjun Yi, University of Alabama at Birmingham; Inmaculada A Aban, The University of Alabama at Birmingham
10:50 AM Using Log Cauchy Priors for Modeling Sparsity Presentation
Zihan Zhu, The University of Arizona; Xueying Tang, The university of Arizona
11:05 AM A Comparison of Bayesian Multivariate Versus Univariate Normal Regression Models for Prediction
Joyee Ghosh, The University of Iowa
11:20 AM A Bayesian Linear Mixed Model for Bi-Level Feature Selection
Daniel Baer, University of Pennsylvania; Andrew Booth Lawson, Medical University of South Carolina; Yeonhee Park, University of Wisconsin-Madison; Sharon Xie, University of Pennsylvania ; Andreana Benitez , Medical University of South Carolina; The ADNI, The Alzheimer's Disease Neuroimaging Initiative
11:35 AM A Bayesian Methodology for Estimation for Sparse Canonical Correlation
Siddhesh Kulkarni, University of Louisville; Subhadip Pal, University of Louisville; Jeremy Gaskins, University of Louisville
11:50 AM For High-Dimensional Hierarchical Models, Consider Exchangeability of Effects Across Covariates Instead of Across Data Sets
Brian Trippe, Massachusetts Institute of Technology; Hilary Finucane, Broad Institute; Tamara Broderick, Massachusetts Institute of Technology
12:05 PM Floor Discussion
 
 

456 * !
Wed, 8/10/2022, 2:00 PM - 3:50 PM CC-204B
Exploiting Lower-Dimensional Structure in Gaussian Process Regression — Invited Papers
Section on Bayesian Statistical Science, International Indian Statistical Association, International Society for Bayesian Analysis (ISBA)
Organizer(s): Sanvesh Srivastava, Department of Statistics and Actuarial Science
Chair(s): Terrance D Savitsky, U.S. Bureau of Labor Statistics
2:05 PM A Gaussian Process Framework for Modeling with Network Inputs
Nathaniel Josephs, Yale University; Lizhen Lin, The University of Notre Dame; Steven Rosenberg, Boston University; Eric Kolaczyk, Boston University
2:35 PM Bayesian Heavy-Tailed Density Estimation
Surya T. Tokdar, Duke University; Erika Cunningham, Unaffiliated; Sheng Jiang, University of California Santa Cruz
3:05 PM Classification Trees for Imbalanced Data: Surface-to-Volume Regularization
Yichen Zhu, Duke University; Cheng Li, National University of Singapore; David Dunson, Duke University
3:35 PM Floor Discussion
 
 

475 * !
Wed, 8/10/2022, 2:00 PM - 3:50 PM CC-202B
Advancing Innovative RWE Analytics in Drug Development — Topic Contributed Papers
Biopharmaceutical Section, Section on Bayesian Statistical Science, Committee on Applied Statisticians, Text Analysis Interest Group
Organizer(s): Haijun Ma, .
Chair(s): Haijun Ma, .
2:05 PM Defining Causal Questions for a Single-Arm Trial with an External Control Arm: An Application of the Target Trial Framework in Oncology
Lisa Hampson, Novartis Pharma AG, Switzerland; Evgeny Degtyarev, Novartis Pharma AG
2:25 PM Causal Effect Machine Learning Analyses Using Model Averaging
Alan Brnabic, Eli Lilly; Anthony Zagar, Eli Lilly
2:45 PM Applying Bayesian Modeling for Reproducibility Issues Between RCT and RWE
Xiang Zhang, CSL Behring; James Stamey, Baylor University
3:05 PM Analysis of Biosimilar Regulatory Review and Approval Texts from the FDA and the EMA
Akash Jayesh Gosai, Viatris; Joseph Cook, Viatris
3:25 PM Discussant: Samiran Ghosh, The University of Texas Health Science Center at Houston
3:45 PM Floor Discussion
 
 

501
Thu, 8/11/2022, 8:30 AM - 10:20 AM CC-143B
Bayesian Penalized Likelihood Methods for Gaussian Graphical Models — Invited Papers
Section on Bayesian Statistical Science, Section on Nonparametric Statistics, Section on Statistical Computing
Organizer(s): Abhra Sarkar, The University of Texas at Austin
Chair(s): Veronica J Berrocal, University of California
8:35 AM New Directions in Bayesian Shrinkage for Structure Learning
Ksheera Sagar K. N. , Purdue University; Sayantan Banerjee, Indian Institute of Management Indore; Jyotishka Datta, Virginia Tech; Anindya Bhadra, Purdue University
9:05 AM Bayesian Scalable Precision Factor Analysis for Massive Sparse Gaussian Graphical Models
Noirrit Kiran Chandra, The University of Texas at Austin; Abhra Sarkar, The University of Texas at Austin; Peter Mueller, The University of Texas at Austin
9:35 AM Quantile Graphical Models: A Bayesian Approach
Nilabja Guha, University of Massachusetts Lowell; Veera Baladandayuthapani, University of Michigan; Bani Mallick, Texas A&M University
10:05 PM Floor Discussion
 
 

536 * !
Thu, 8/11/2022, 10:30 AM - 12:20 PM CC-201
Advanced Bayesian Methods for Modern Clinical Trials — Invited Papers
International Society for Bayesian Analysis (ISBA), Biopharmaceutical Section, Section on Bayesian Statistical Science
Organizer(s): Yuan Ji, The University of Chicago
Chair(s): Yanxun Xu, Johns Hopkins University
10:35 AM Estimating the Design Operating Characteristics in Bayesian Adaptive Clinical Trials Presentation
Shirin Golchi, McGill University
10:55 AM On Bayesian Sequential Clinical Trial Designs
Tianjian Zhou, Colorado State University; Yuan Ji, The University of Chicago
11:15 AM The Use of External Control Data for Predictions and Futility Interim Analyses in Clinical Trials
Lorenzo Trippa, DFCI
11:35 AM Bayesian Nonparametric Common Atoms Regression for Generating Synthetic Controls in Clinical Trials
Peter Mueller, The University of Texas at Austin; Noirrit Kiran Chandra, The University of Texas at Austin; Abhra Sarkar, The University of Texas at Austin
11:55 AM Discussant: Yuan Ji, The University of Chicago
12:15 PM Floor Discussion
 
 

541 * !
Thu, 8/11/2022, 10:30 AM - 12:20 PM CC-202B
Bayesian Design in Clinical Trial and Some Challenging Issues — Topic Contributed Papers
Section on Bayesian Statistical Science, Biopharmaceutical Section, International Society for Bayesian Analysis (ISBA)
Organizer(s): Fei Wang, Boehringer Ingelheim
Chair(s): Guan Xing, Gilead
10:35 AM Practical Steps for Dynamic Borrowing of Historical Control Data in Clinical Trials
Farid Jamshidian, Gilead Sciences; Ron Xiaolong Yu, Gilead Sciences
10:55 AM Exploring Approaches to Sample Size Determination Within a Bayesian Framework
Jane Pan, University of California, Los Angeles
11:15 AM Predicting Outcomes of Phase III Oncology Trials with Bayesian Mediation Modeling of Tumor Response
Xun Jiang, Amgen; Jie Zhou, Novartis; Brian P Hobbs, The University of Texas; Peng N/A Wei, The University of Texas MD Anderson Cancer Center; Amy Xia, Amgen
11:35 AM Bayesian Design in Clinical Trial and Some Challenging Issues
Fei Wang, Boehringer Ingelheim
11:55 AM Perceived Barriers and Educational Preferences Among Medical Researchers Involved in Drug Development
Jennifer Clark, FDA; BSWG Medical Outreach Subteam, DIA
12:15 PM Floor Discussion
 
 

557
Thu, 8/11/2022, 10:30 AM - 12:20 PM CC-204A
New Directions in Bayesian Methods for Longitudinal and Graph Data — Contributed Papers
Section on Bayesian Statistical Science
Chair(s): Sameer Deshpande, UW-Madison
10:35 AM Inference of Random Dot Product Graphs with a Surrogate Likelihood Function
Dingbo Wu, Indiana University; Fangzheng Xie, Indiana University
10:50 AM Methodological Improvement of Bayesian Additive Regression Trees for Classification Problems Using Novel Priors or Model Averaging Presentation
Xiao Li, Medical College of Wisconsin; Rodney A Sparapani, Medical College of Wisconsin; Purushottam W Laud, Medical College of Wisconsin; Brent R Logan, Medical College of Wisconsin
11:05 AM Constrained Bayesian Hierarchical Models for Gaussian Data: A Criterion Based Approach
Qingying Zong, Florida state university; Jonathan R Bradley, Florida State University
11:20 AM A Bayesian Hierarchical Spatially Varying Coefficients Model for Longitudinal Structural Data in Glaucomatous Eyes
Erica Su, UCLA Biostatistics; Andrew Holbrook, UCLA Biostatistics; Robert Erin Weiss, UCLA Biostatistics; Kouros Nouri-Mahdavi, UCLA Stein Eye Institute
11:35 AM Bayesian Joint Modeling and Selection Among Many Biomarkers Measured Longitudinally
Soumya Sahu, Biostatistics, University of Illinois Chicago; Sanjib Basu, Biostatistics, University of Illinois Chicago; Jiehuan Sun, Biostatistics, University of Illinois Chicago; Joelle Hallak, Ophthalmology, Illinois Eye and Ear Infirmary, University of Illinois Chicago; AbbVie
11:50 AM A Bayesian Bernoulli-Exponential Joint Model for Longitudinal Outcomes and Informative Time Points
Michael Safo Oduro, University of Northern Colorado; Khalil Shafie, University of Northern Colorado
12:05 PM Individualized Inference Using Bayesian Quantile Directed Acyclic Graphical Models
Ksheera Sagar K. N. , Purdue University; Yang Ni, Texas A&M University; Veera Baladandayuthapani, University of Michigan; Anindya Bhadra, Purdue University