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Topic-Contributed Paper Session

Advances in experimental designs and observational studies with complex treatments

Thu, Aug 6, 8:30 AM - 10:20 AM Room CC-258C Thomas M. Menino Convention & Exhibition Center

Souhardya SenguptaOrganizerKosuke ImaiOrganizerPeng DingChair

Social Statistics Section co: Government Statistics Sectionco: Business and Economic Statistics Section Applied

5 Presentations

Adaptive Experimental Design for Efficient Causal Estimators under Neighborhood and Temporal Interference

8:35 AM - 9:55 AM

Fei Fang (Yale University)

Co-authors: Laura Forastiere (Yale University)

Causal inference in networks Randomized design and analysis Interference

Always-On Experiments

8:55 AM - 9:15 AM

Ricardo Sandoval (University of California, Berkeley)

causal inference sequential hypothesis tests testing by betting average treatment effect

Hypothesis Testing for Detecting Network Interference in Randomized Experiments

9:15 AM - 9:35 AM

Christopher Harshaw

causal inference network experiments interference hypothesis testing

Low-rank Covariate Balancing Estimators under Interference

9:35 AM - 9:55 AM

Souhardya Sengupta (Harvard University)

Co-authors: Kosuke Imai (Harvard University), Georgia Papadogeorgou

Anonymous interference Average treatment effects causal inference covariate balancing partial interference spillover effects

Using a Two-Parameter Sensitivity Analysis Framework to Efficiently Combine Randomized and Non-randomized Studies

9:55 AM - 10:15 AM

Ruoqi Yu (University of Illinois Urbana Champaign)

Co-authors: Bikram Karmakar (University of Wisconsin-Madison), Jessica Vandeleest (University of California Davis), Eleanor Bimla Schwarz (University of California San Francisco)

Causal inference Generalizability bias Matching Sensitivity analysis Unmeasured confounding

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