361
Tue, 7/30/2019,
11:35 AM -
12:20 PM
CC-Hall C
SPEED: Biometrics - Methods and Application, Part 2 — Contributed Poster Presentations
Biometrics Section , Section on Bayesian Statistical Science
Chair(s): Katherine E Irimata, National Center for Health Statistics
Oral Presentations
for this session.
1:
Development of an International Prostate Cancer Risk Tool Integrating Data from Multiple Heterogeneous Cohorts
Donna Ankerst, Technical University of Munich ; Johanna Tolksdorf, Technical University of Munich
2:
An Exponential Effect Persistence Model for Intensive Longitudinal Data
Claude Setodji, RAND Corporation ; Steven C. Martino, RAND Corporation; Michael S. Dunbar, RAND Corporation; William G. Shadel, RAND Corporation
3:
Analyzing Pre-Post Randomized Studies with One Post-Randomization Score Using Repeated Measures and ANCOVA Models
Fei Wan, University of Arkansas for Medical Sciences
4:
Spectral Parameterization, Diagnostics, and Remedies for Confounding of Fixed Effects by Random Effects
Patrick Schnell, Ohio State University ; Maitreyee Bose, Amgen
5:
Differential Abundance Analyzes of Pre- and Post-Metabolomic Data with Steroid Treatment for Bronchopulmonary Dysplasia
Prabhakar Chalise, University of Kansas Medical Center ; Tamorah R Lewis, Children’s Mercy Hospital, University of Missouri Kansas City
7:
SignNets: Fine Tuning Gene-Gene Similarity Metrics in Biological Systems
Crystal Shaw, UCLA ; Vinayagam Arunachalam, Pfizer, Inc.; Jadwiga R Bienkowska, Pfizer, Inc.
8:
To EM or Not to EM: Updated Estimation of the Probability of Clonal Relatedness of Pairs of Tumors in Cancer Patients
Audrey Mauguen, Memorial Sloan Kettering Cancer Center ; Venkatraman E. Seshan, MSKCC; Irina Ostrovnaya, MSKCC; Colin Begg, Memorial Sloan Kettering Cancer Center
9:
Is it ‘random’ or ‘haphazard’? Demonstrating Effects of Nonrandom Allocation by Simulation
Penny Reynolds, University of Florida College of Medicine
10:
Estimating Optimal Treatment Regime to Maximize Restricted Mean Survival Time
Sanhita Sengupta, University of Minnesota
11:
Item Response Theory Models for Survival Analysis and the Detection of Treatment Efficacy
Charlie Iaconangelo, Pharmerit International
12:
Similarity-Based Probability Weighted Learning for Individual Treatment Rule Estimation
Jinchun Zhang, New York University ; Andrea B Troxel, NYU School of Medicine; Eva Petkova, New York University
13:
Multivariate Longitudinal Data from Eyes - Microperimetry Macular Sensitivity Loss in Patients with Stargardt Disease
Zhengfan Wang, UMASS-Amherst ; Xiangrong Kong, Johns Hopkins University
14:
On Powerful Exact Nonrandomized Tests for the Poisson Two-Sample Setting
Stefan Wellek, CIMH Mannheim/University of Heidelberg, Germany/University of Mainz, Germany
15:
Survey Calibration to Improve the Efficiency of Pure Risk Estimates from Case-Control Samples Nested in a Cohort
Yei Eun Shin, National Cancer Institute ; Ruth Pfeiffer, National Cancer Institute; Barry Graubard, National Cancer Institute; Mitchell Henry Gail, National Cancer Institute, Division of Cancer Epidemiology and Genetics
16:
Two-Way Partial AUC and Its Properties
Kun Lu, Princeton University ; Hanfang Yang, Renmin University of China; Xiang Lv, University of California, Berkeley; Feifang Hu, George Washington University
17:
Relative Risk Estimation in Clustered/Longitudinal Data Using Generalized Estimating Equations (GEE)
Chao Zhu, Menzies Institute for Medical Research, University of Tasmania ; David W Hosmer, University of Vermont; Jim Stankovich, School of Medicine, University of Tasmania, Central Clinical School, Monash University; Karen Wills, Menzies Institute for Medical Research, University of Tasmania ; Leigh Blizzard, Menzies Institute for Medical Research, University of Tasmania
18:
Variance Estimation When Combining Inverse Probability Weighting and Multiple Imputation in Electronic Health Records-Based Research
Tanayott Thaweethai, Harvard T.H. Chan School of Public Health ; Sebastien Haneuse, Harvard T.H. Chan School of Public Health
19:
Bayesian Generalized Mixed-Effect Modeling of Conway-Maxwell Poisson Data
Morshed Alam, University of Nebraska Medical Center ; Meza Jane, University of Nebraska Medical center; Yeongjin Gwon, University of Nebraska Medical Center
