Legend:
CC = Vancouver Convention Centre
F = Fairmont Waterfront Vancouver
* = applied session ! = JSM meeting theme
258
Mon, 7/30/2018,
2:00 PM -
2:45 PM
CC-West Hall B
SPEED: Causal Inference and Related Methodology — Contributed Poster Presentations
Section on Statistics in Epidemiology
Chair(s): Paul McNicholas, McMaster University
Oral Presentations
for this session.
21:
Estimating Average Causal Treatment Effects Utilizing Fractional Imputation When Confounders Are Subject to Missingness
Nathaniel Corder, North Carolina State University ; Shu Yang, North Carolina State University
23:
A Comparison of Methods to Estimate Survival Curves Under Time-Varying Treatments
Lucia C. Petito, Harvard T.H. Chan School of Public Health ; Sonja A. Swanson, Erasmus Medical Center; Miguel Hernan, Harvard School of Public Health
24:
Sufficient Cause Interaction for Ordinal and Categorical Outcomes
Jaffer Zaidi ; Tyler VanderWeele, Harvard University
25:
Combining Inverse Probability Weighting and Multiple Imputation to Adjust for Selection Bias 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; David Arterburn, Kaiser Permanente Washington Health Research Institute
26:
Efficient Design and Analysis of Cluster Randomized Trials
Hengshi Yu, University of Michigan, Ann Arbor ; Fan Li, Duke Univeristy; John A. Gallis, Duke University; Elizabeth L. Turner, Duke Global Health Institutes
27:
Maximum Likelihood Estimation of the K Parameter in the Poly-K Trend Test for Time-to-Event Data
Anna Korpak, VA ERIC ; Barbara McKnight, University of Washington
28:
A Bayesian Nonparametric Approach to Estimate Causal Effects of Mediation in the Presence of Nonignorable Missingness
Dandan Xu, US Food and Drug Administration ; Michael Daniels, University of Florida
29:
Multivariate Mediation Analysis with a Multi-Categorical Exposure Variable: An Application to Explore Racial and Ethnic Disparities in Obesity
Qingzhao Yu, Louisiana State University Health Sciences Ctr ; Lin Zhu, Louisiana State University Health Sciences Ctr; Bin Li, Louisiana State University
30:
Balancing Scores Weighing Methods and Sensitivity Analysis to Unfold Health Disparity
Chen-Pin Wang, University of Texas Health San Antonio
31:
Power Evaluation for Covariate Balancing Propensity Score Methods
Byeong Yeob Choi, University of Texas Health Science Center at San Antonio ; Chen-Pin Wang, University of Texas Health San Antonio; Joel Michalek, University of Texas Health Science Center at San Antonio; Jonathan Gelfond, University of Texas Health San Antonio
32:
Embedding Observational Studies into Hypothetical Fractional-Factorial Experiments
Nicole Pashley, Harvard University ; Marie-Abele Bind, Harvard University
33:
Using Validation Data to Adjust the Inverse Probability Weighting Treatment Effect Estimator for Misclassified Treatment
Danielle Braun, Harvard T. H. Chan School of Public Health ; Corwin Zigler, Harvard T.H. Chan School of Public Health; Francesca Dominici, Harvard T. H. Chan School of Public Health; Malka Gorfine, Tel Aviv University
34:
Leveraging Multiple Study Designs and Statistical Methods to Evaluate Comparative Effectiveness of Asthma Medications
Tebeb Gebretsadik, Vanderbilt University Medical Center ; Pingsheng Wu, Vanderbilt University; Rees L Lee, U. S. Navy; Amber M Evans, Health ResearchTX LLC; Tan Ding, Vanderbilt University Medical Center; Nicholas M Sicignano, Health Research Tx ; Ann Wu, Harvard Medical School; Carlos Iribarren, Kaiser Permanente Division of Research; Butler Melissa, Kaiser Permanente; Chang Yu, Vanderbilt University Medical Center; William Dupont, Vanderbilt University Medical Center; Christina Fox, Health ResearchTx; Tina V Hartert, Vanderbilt University Medical Center
36:
Gaussian Process Propensity Scores for Multiple Treatment Regimes
Brian Vegetabile, UC Irvine ; Daniel L. Gillen, University of California, Irvine; Hal Stern, University of California, Irvine
37:
Accounting for Variation in Instrumental Effect Estimates Leads to More Precise Estimates of Causal Effects in MR Studies
Richard Barfield, Fred Hutchinson Cancer Research Center ; Li Hsu, Fred Hutchinson Cancer Research Center, USA
38:
Estimating Causal Effect by Difference in Difference via Random Forest
Tomoshige Nakamura, Graduate School of Science and Technology, Keio University ; Mihoko Minami, Keio University
39:
Assessing Therapeutic Equivalence of Brand and Generic Drugs Using Observational Data
Lamar Hunt, Johns Hopkins Bloomberg SPH & OptumLabs Visiting Fellows ; Daniel Scharfstein, Johns Hopkins University; Irene Murimi, Johns Hopkins Bloomberg SPH & OptumLabs Visiting Fellows; Jodi Segal, Johns Hopkins Bloomberg SPH & OptumLabs Visiting Fellows; Ravi Varadhan, Johns Hopkins University; Ramin Mojtabai, Johns Hopkins Bloomberg SPH