88
Sun, 7/28/2019,
5:05 PM -
5:50 PM
CC-Hall C
SPEED: Causal Inference and Related Methodology Part 2 — Contributed Poster Presentations
Section on Statistics in Epidemiology
Chair(s): Te-Ching Chen, CDC/NCHS
Oral Presentations
for this session.
1:
Instrumental Variable Estimation of Weighted Local Average Treatment Effects
Byeong Yeob Choi, University of Texas Health Science Center at San Antonio
2:
Two-Stage Residual Inclusion Under the Additive Hazards Model - an Instrumental Variable Approach with Application to SEER-Medicare Linked Data
Andrew Ying, University of California, San Diego ; Ronghui Xu, University of California, San Diego; James Murphy, University of California, San Diego
3:
Xtgeebcv: a Stata Command for Bias-Corrected Sandwich Variance Estimation for GEE Analyzes of Cluster Randomized Trials
John A Gallis, Duke University ; Fan Li, Duke University; Elizabeth L Turner, Duke University
4:
Sensitivity Analysis and the Odds Ratio
Julian Chan, Weber State University
5:
On the Identification of Individual Principal Stratum Direct, Natural Direct and Pleiotropic Effects Without Cross-World Independence Assumptions
Jaffer Zaidi ; Tyler VanderWeele, Harvard University
6:
Mediation Analysis with a Censored Mediator in a Case–control Study
Jian Wang, UT MD Anderson Cancer Center ; Jing Ning, The University of Texas MD Anderson Cancer Center; Sanjay Shete, UT MD Anderson Cancer Center
7:
Conditional Process Analysis: Moderated Mediation Model of Perceived Ethnic Discrimination and Binge Drinking Among Recent Latino Immigrant Youth
Zoran Bursac, Florida International University ; Miguel Angel Cano, Florida International University; Seth J Schwartz, University of Miami
8:
A Modified Partial Likelihood Score Method for Cox Regression with Covariate Error Under the Internal Validation Design
Xin Zhou, Yale School of Public Health ; David Zucker, The Hebrew University of Jerusalem; Xiaomei Liao, AbbVie; Yi Li, University of Michigan School of Public Health; Donna Spiegelman, Yale School of Public Health
9:
Multivariate One-Sided Testing in Matched Observational Studies as an Adversarial Game
Peter Lucas Cohen, Massachusetts Institute of Technology ; Matt A. Olson, The Voleon Group; Colin B. Fogarty, Massachusetts Institute of Technology
10:
Permutation Weighting
Drew Dimmery, Facebook ; David Arbour, Adobe Research
12:
Estimation of Mediation Effect for High-Dimensional Omics Mediators with Application to the Framingham Heart Study
Tianzhong Yang, The University of Minnesota Twin Cities ; Jingbo Niu, Baylor College of Medicine; Han Chen, the University of Texas Health Science Center at Houston; Peng Wei, The University of Texas MD Anderson Cancer Center
13:
Bias and Efficiency in a Matched Observational Study with Varying Cluster Size
Eric KH Chow, Quantitative Sciences Unit, Stanford University School of Medicine ; Rajani Kaimal, Quantitative Sciences Unit, Stanford University School of Medicine; Vedant Pargaonkar, Interventional Cardiology, Stanford University School of Medicine; Sara Bouajila, Stanford University School of Medicine; Katharine Sears-Edwards, Cardiovascular Medicine, Stanford University School of Medicine; Jennifer Tremmel, Interventional Cardiology, Stanford University School of Medicine; Manisha Desai, Stanford University Quantitative Sciences Unit
14:
Testing for Weak Instruments in Two Sample Summary Data Multivariable Mendelian Randomisation
Eleanor Sanderson, University of Bristol ; Jack Bowden, University of Bristol
15:
Estimating Uncertainty in Weighted Competing Risk Analyzes
Amber Hackstadt, Vanderbilt University Medical Center ; Jonathan Chipman, Vanderbilt University; Christianne L. Roumie , Vanderbilt University Medical Center, Veteran Administration Tennessee Valley VA Health ; Adriana M. Hung, Vanderbilt University Medical Center; Jea Young Min , Vanderbilt University Medical Center; Carlos G Grijalva , Vanderbilt University Medical Center; Marie R Griffin, Vanderbilt University Medical Center; Robert Greevy, Vanderbilt University
16:
Person as Population: a Longitudinal View of Single-Subject Causal Inference for Analyzing Self-Tracked Health Data
Eric J. Daza, Stanford Prevention Research Center, Stanford University School of Medicine
17:
Causal Mediation Analysis Using Gradient Boosting Machines: Developing Methods and Software
Brian G. Vegetabile, RAND Corporation ; Donna L. Coffman, Temple University; Daniel F. McCaffrey, Educational Testing Service
18:
Hypothesis Testing in Nonlinear Function on Scalar Regression with Application to Child Growth Study
Mityl Biswas, NC State Univ
19:
Identify Consensus Among Match Makers: a Clustering Aggregation Perspective
Yumin Zhang, Purdue University ; Arman Sabbaghi, Purdue University
