International Day Of Women in Statistics and Data Science: Full Schedule

Registration opens August 15th at www.idwsds.org.

You will be able to validate your attendance (Check-In to sessions) using your personal schedule.

13:00 UTC

S404 - Coordinating Evidence for Better Research Design: Priors, Assumptions, and Scientific Judgment

Tuesday October 6, 2026 13:00 - 14:00 UTC

This session examines how scientific judgment can be made explicit in research design and decision making with mixed methods evidence, causal knowledge, expert elicitation, and Bayesian priors. Noor Qaragholi opens by showing how qualitative and quantitative evidence can inform strong, untestable causal assumptions in study design, illustrated through CACE estimation in a randomized behavioral intervention with substantial noncompliance. Utkarshani Jaimini then turns to Causal Neuro-Symbolic AI, a framework for building systems that are explainable, interpretable, and causally aware rather than limited to correlational pattern matching. Her work spans knowledge representation, causal inference, and applied machine learning. Anna Heath discusses expert elicitation for Bayesian clinical trial design, focusing on remote, real time exercises that help experts translate experience into probabilistic statements for prior distributions. Lu (Maggie) Qian closes by examining how Bayesian trial design can make scientific judgment explicit without allowing prior choice to become opaque, drawing on FDA guidance and reverse-Bayes methods as an audit tool. Together, the talks show how making assumptions and priors explicit can strengthen research design and support credible, decision relevant conclusions.

Speakers

Noor Qaragholi

The Policy & Research Group

Noor Qaragholi is a public health researcher with 15 years of experience conducting qualitative, quantitative, and mixed methods research to improve health programs, services, and systems. As a Senior Research Analyst at The Policy & Research Group, Dr. Qaragholi leads large-scale... Read More →

Utkarshani Jaimini

University of Michigan Dearborn

Utkarshani Jaimini is an Assistant Professor in the Department of Computer and Information Science at the University of Michigan-Dearborn, where she joined as a faculty in Fall 2025. She holds her doctoral degree from the University of South Carolina. Her research lies at the intersection... Read More →

Lu Qian

Zetyra, LLC

Lu (Maggie) Qian is an independent biostatistician and founder of Evidence in the Wild and Zetyra. Her work focuses on Bayesian and adaptive clinical trial design, regulatory alignment, prior specification, prior-data conflict, and operating characteristics of composed adaptive pipelines... Read More →

Anna Heath

The Hospital for Sick Children

Dr. Heath is a Scientist at The Hospital for Sick Children (SickKids), Toronto, an Associate Professor at University of Toronto and Honorary Research Fellow at University College London, UK. She is the Canada Research Chair in Statistical Trial Design. She arrived at SickKids in 2018... Read More →

Chairs/Hosts

Elizabeth Eisenhauer

Organizers

Elizabeth Eisenhauer

S404 Abstracts pdf

Tuesday October 6, 2026 13:00 - 14:00 UTC
Zoom Room #4

Invited Session, Technical Statistical Session

Session ID 404

International Day Of Women in Statistics and Data Science

13:00 UTC

Noor Qaragholi

Utkarshani Jaimini

Lu Qian

Anna Heath

Elizabeth Eisenhauer

Elizabeth Eisenhauer

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