Poster Titles and Locations

Below is the list of accepted poster presenters with titles and numbered locations on the posterboards.  

The poster session will be held on Thursday evening from 5:00 pm to 7:00 pm in the New Residence Hall, Room B.   The list of poster presenters and titles can be found below with their corresponding poster information. 

Presenters will be able to set their posters up during the lunch break on Thursday.  

 

Poster Number Name Title
1 Meg Fluharty Educational differentials in domain specific physical activity by ethnicity, age, and gender: findings from Understanding Society, The UK Household Longitudinal Study.
2 Eli Sherman Friendship Interventions
3 Peter Lucas Cohen Bootstrap prepivoting for finite population causal inference
4 Jiaxi Yang Small sample criterion for covariate balance in rerandomization
5 Brian L. Egleston Using Summary Comorbidity Measures for Prognosis and Survival Treatment Effect Estimation
6 Nicholas J Parr Latent Class Analysis with Inverse Propensity Weighting: Assessing the Causal Relation of University-setting Sexual Assault with Depression, Anxiety, Substance Use, and Loss of Control Eating
7 Harsh Parikh MALTS: Matching After Learning to Stretch
8 Nadia Sourial How robustly do we verify the assumptions of the causal inference framework? Qualitative methods can provide a more in-depth and informed assessment
9 Rebecca Taylor Studying the effect of ship disturbance on walrus behavior: an uncommon use of causal inference techniques
10 Spencer Woody Characterizing treatment effect heterogeneity via posterior summarization
11 Kuan Liu Estimation of causal effects with repeatedly measured outcomes in a Bayesian framework
12 Mariel Finucane Beyond Treatment Versus Control: How Bayesian Hierarchical Models Make Factorial Experiments Feasible in Education Research
13 Etsuji Suzuki Causal diagrams for propensity score methods
14 Naoki Egami Identification of Causal Diffusion Effects Using Stationary Causal Directed Acyclic Graphs
15 Thomas Leavitt Design-Based Bayesian Inference for Causal Effects
16 Chen Lu Non-Parametric Regression Adjustments for Difference-in-Differences Estimation
17 Evan Rosenman Designing Experiments to Complement Observational Studies
18 Bikram Karmakar Effect of Medical Marijuana Laws on Traffic Fatalities: An Evidence Factors Analysis in a Difference-in-Differences Study
19 Shuangning Li Balancing Covariates in Regression Discontinuity Designs
20 Tianyang Zhang Comparing methods for estimation of heterogeneous treatment effects using observational data from education databases
21 Noemi Exploring heterogeneous treatment effects to inform the targeting of national health insurance programmes
22 Jiongyi Cao Discovering Causal Heterogeneity in Medicaid Utilization with a Tree-Based Machine Learning Method
23 Lucy Mosquera Comparing the Performance of Instrumental Variable Methods When Estimating the Causal Effect of Treatment In Pragmatic Trials with Non-Compliance
24 Jiaqing Zhang A novel instrumental variable approach to estimate nested treatment heterogeneity
25 Sheng Wang Weak-Instrument Robust Estimators and Tests for Two-Sample Summary Mendelian Randomization
26 Matthew Tudball An interval estimation approach for selection bias in OLS and IV studies
27 Kathleen Kennedy-Turner Using causal mediation based on counterfactuals in longitudinal analyses for child development: Two data case studies
28 Christiane Didden Counterfactual-based mediation analysis in the social sciences.: An analysis of the gender pay gap.
29 Oliver Hines A new test for an indirect effect in the confounded single mediator problem using doubly robust G-estimation
30 Nima Hejazi Nonparametric-efficient causal mediation analysis for stochastic interventions
31 Shuxi Zeng Causal Mediation Analysis for Sparse and Irregular Longitudinal Data
32 Andrew Ying Causal Effects on Birth Defects with Missing by Terathanasia
33 Jaron Lee Computationally Efficient Analysis of Randomized Trials with Non-Monotone Missing Binary Outcomes
34 Falco Joannes Bargagli Stoffi Heterogeneous causal effects with imperfect compliance. A novel Bayesian machine learning approach
35 Lina Montoya Performance of Super-Learner Based Optimal Dynamic Rule Estimation
36 Ranjani Srinivasan Pathway Dependent Causal Models
37 Eli Ben-Michael Causal inference with simple models and complex features
38 Edward Wu The P-LOOP Estimator: Covariate Adjustment for Paired Experiments
39 Ismaila Balde Generalized Outcome Adaptive Lasso: Variable Selection for High Dimensional Causal Inference
40 Razieh Nabi Learning Optimal Fair Policies
41 Leah Comment Nonparametric causal inference for semicompeting risks using Bayesian Additive Regression Trees (BART)
42 Kevin P. Josey A Framework for Covariate Balance using Bregman Distances
43 Amelia J. Averitt Adversarial training to learn feature-balancing weights for cohorts: The Counterfactual Chi-GAN
44 Tyrel Stokes Model Selection under Unmeasured Confounding: Understanding the role of Bias Amplification
45 Karthik Rajkumar Ridge regularization for Mean Squared Error Stabilization in Regression with Weak Instruments
46 Karthik Rajkumar Exact p-values and partial identification of treatment effects in a regression discontinuity design with manipulation
47 Huaqing Zhao Principal Components and Propensity Scores (PCAPS): Adjustment for Confounding in High-dimensional Observational Studies
48 Michele Santacatterina Optimal balancing of time-dependent confounders for marginal structural models
49 Rui Lu Two-step BART: a generalized framework to estimate average treatment effects when treatment is a latent class
50 Shirley Liao Bayesian additive regression trees for confounder selection in high-dimentional settings
51 Yue You Application of targeted learning to assess the performance of a diabetes care program, in terms of quality of care and health outcomes
52 Michael Schomaker Time-dependent causal dose‰ÛÒresponse curves under limited data support ‰ÛÒ An example from HIV treatment research
53 Ted Westling Causal Isotonic Regression
54 Ruoqi Yu Matching Methods for Observational Studies Derived from Large Administrative Databases
55 Drew Dimmery Permutation Weighting
56 Shu Yang Semiparametric efficient estimation of structural nested mean models with irregularly spaced observations
57 Alexander D’Amour On Multi-Cause Causal Inference with Unobserved Confounding: Counterexamples, Impossibility, and Alternatives
58 Yan Leng Observational causal inference using network information
59 Yan Leng Estimating social influence with homophilous latent positions
60 Jose Itamar Mendes de Souza Junior Causal Inference and Ad Hoc Social Networks for Health Professional Societies
61 Rohit Bhattacharya Causal Inference Under Interference and Network Uncertainty
62 Rohit Bhattacharya Identification In Missing Data Models Represented By Directed Acyclic Graphs
63 Sebastian Martinez Causal Inferential Dynamic Network Analysis for Public Health: STASH
64 Zahide Alaca Regression-with-residuals estimation of marginal effects: A method of adjusting for treatment-induced confounders that may also be effect modifiers
65 Michael Lingzhi Li Experimental Evaluation of Individualized Treatment Rules
66 Hao Sun On estimation of optimal treatment regimes for maximizing quality adjusted lifetime
67 Jonathan Stiles Inference For the Smoothed Proportion Whose Average Treatment Exceeds a Threshold
68 Alexander Franks Latent Confounder Approaches to Sensitivity without Observable Implications
69 Aurelien Bibaut Randomization inference and sensitivity analysis in two-stage observational studies with interference
70 Siyu Heng Increasing Power for Observational Studies of Aberrant Response: An Adaptive Approach
71 Matteo Bonvini Sensitivity Analysis via the Proportion of Unmeasured Confounding
72 David Choi Constrasts attributable to treatment: what can be learned with no assumptions on interference?
73 James Bisbee Non-Parametric Synthetic Controls via Implicit Randomization
74 Alan Mishler

Counterfactual Fairness in the Actual World

74 Amanda Coston

Doubly-robust algorithmic risk assessment