MAY 14 – 17, 2024 SEATTLE, WASHINGTON
![]() |
![]() |
![]() |
![]() |
32-P | Post-ion inference for causal effects after causal discovery | Ting-Hsuan Chang | ![]() |
![]() |
|||
34-P | Causal Discovery in Directed, Possibly Cyclic, Graphical Models | Pardis Semnani | ![]() |
![]() |
|||
41-P | A Decision-Theoretic Framework for Sample Selection in Randomized Experiments | Yuchen Hu | ![]() |
![]() |
|||
42-P | Regression-Based Proximal Causal Inference | Jiewen Liu | ![]() |
![]() |
|||
43-P | Credible Evidence of Gender Discrimination Using Instrumental Inequality | Jiwoo Kim | ![]() |
![]() |
|||
67-P | Operational Challenges in Scaling Randomized Trials: The Role of Capacity Constraints | Hannah Li | ![]() |
![]() |
|||
83-P | Online Learning in the Face of Unemployment | Kiet Le | ![]() |
![]() |
|||
104-P | Independent-Set Design of Experiments for Estimating Treatment and Spillover Effects under Network Interference | Chencheng Cai | ![]() |
![]() |
|||
105-P | Quasi-randomization tests for network interference | Supriya Tiwari | ![]() |
![]() |
|||
130-P | Causal Inference with High-dimensional Discrete Covariates | Zhenghao Zeng | ![]() |
![]() |
|||
141-P | Survival after hospitalization: Constructing counterfactual time-to-event outcomes for difference-in-differences studies | Laura Hatfield | ![]() |
![]() |
|||
146-P | Sequential Synthetic Difference in Differences | Aleksei Samkov | ![]() |
![]() |
|||
148-P | Beyond parallel trends: unifying difference-in-differences and synthetic controls | Denis Agniel | ![]() |
![]() |
|||
178-P | Efficient combination of observational and experimental datasets with structural information about outcome mean functions | Harrison Li | ![]() |
![]() |
|||
203-P | Flexibly Estimating and Interpreting Heterogeneous Treatment Effects of Laparoscopic Surgery for Cholecystitis Patients | Luke Keele | ![]() |
![]() |
|||
206-P | Causal Q-Aggregation for CATE Model Selection | Hui Lan | ![]() |
![]() |
|||
209-P | Qini Curves for Multi-Armed Treatment Rules | Erik Sverdrup | ![]() |
![]() |
|||
210-P | Active Feature Acquisition in Precision Medicine | Michael Valancius | ![]() |
![]() |
|||
244-P | Manipulating a Continuous Instrumental Variable: Algorithm, Partial Identification Bounds, and Inference under Randomization and Biased Randomization Assumptions | Min Haeng Cho | ![]() |
![]() |
|||
247-P | Identifying Causal Effects of Nonbinary, Ordered Treatments using Multiple Instrumental Variables | Nadja van t Hoff | ![]() |
![]() |
|||
248-P | Online Education: Savior or Saboteur of Productivity in the Modern Era? | Octavio M. Aguilar | ![]() |
![]() |
|||
250-P | Impact of Prosecutorial Systems on Charging Decisions: Application of the Instrumental Variable Method | Takuma Iwasaki | ![]() |
![]() |
|||
282-P | Strategic Decision-Making in the Presence of Information Asymmetry: Provably Efficient RL with Algorithmic Instruments | Mengxin Yu | ![]() |
![]() |
|||
293-P | Statistical Learning for Constrained Functional Parameters in Infinite-Dimensional Models with Applications in Fair Machine Learning | Razieh Nabi | ![]() |
![]() |
|||
313-P | Gaussian Processes for Social Scientists: A powerful tool for addressing model-dependency and uncertainty | Soonhong Cho | ![]() |
![]() |
|||
319-P | Comprehensive Causal Machine Learning | Jana Mareckova | ![]() |
![]() |
|||
351-P | Powerful Partial Conjunction Hypothesis Testing via Conditioning | Biyonka Liang | ![]() |
![]() |
|||
360-P | Using a separable effects model to overcome extreme positivity violation and distinguish the causal effects of surgery and anesthesia | Amy Pitts | ![]() |
![]() |
|||
362-P | Separable pathway effects for semi-competing risks in multi-state models, with application to leukemia data | Yuhao Deng | ![]() |
![]() |
|||
453-P | Test-Negative Designs with Various Reasons for Testing: Statistical Bias and Solution. | Mengxin Yu | ![]() |
![]() |
|||
457-P | Identifying sparse treatment effects in high-dimensional outcome spaces | Yujin Jeong | ![]() |
![]() |
|||
463-P | Causal Inference for Balanced Incomplete Block Designs | Taehyeon Koo | ![]() |
![]() |
|||
468-P | Rothman sufficient cause urn analysis of the truncation by death problem | Jaffer Zaidi | ![]() |
![]() |
|||
480-P | Blessing of Multiple Control Groups in Fuzzy Regression Discontinuity Designs: Evaluating Extended Time Accommodations | Youmi Suk | ![]() |
![]() |
|||
498-P | A Split-Sampling Framework for Powerful Design of Observational Studies under Unmeasured Confounding | William Bekerman | ![]() |
![]() |
|||
512-P | Single Proxy Synthetic Control | Chan Park | ![]() |
![]() |
|||
514-P | A new perspective on synthetic controls | Yujin Jeong | ![]() |
![]() |
|||
515-P | The Perils of Nonstationary Data in Synthetic Control Applications | Hongyu Mou | ![]() |
![]() |
|||
547-P | Minimax Optimal Estimates of Individual Causal Effects in Panel Data under Heterogeneous Two Way Fixed Effects Models | Calvin Tolbert | ![]() |
![]() |
|||
552-P | Local Longitudinal Modified Treatment Policies | Herbert Susmann | ![]() |
![]() |
|||
554-P | Two-Step Targeted Minimum-Loss Based Estimation for Non-Negative Two-Part Outcomes | Nicholas Williams | ![]() |
![]() |
|||
558-P | Off-Policy Learning of Content Promotions: Optimizing Digital Distribution Channels | Joel Persson | ![]() |
![]() |
MAY 14 – 17, 2024 SEATTLE, WASHINGTON
![]() |
Digital Object Identifier. Official code used to identify documents published on internet; similar to ISBN for books. You may use this code to reference your poster in future scientific publications or CVs. It can be found from anywhere in the world. ![]() To find the poster page, log onto www.medra.org and enter the DOI, or enter in your internet browser https://dx.doi.org/ followed by the DOI string asigned to your congress. ![]() |
![]() |
||
![]() |
|