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.

15:00 UTC

S213 - Causal Outside the Classroom: How is causal inference used in day-to-day working environments?

Tuesday October 6, 2026 15:00 - 16:00 UTC

Causal inference is a term that has become a buzzword and a popular field of research in many fields recently, and arises often in statistics. Causal methodologies can sound overly complex to many collaborators, and others may fixate on the need to have causal results from all possible studies. New researchers and scientists are left with questions of how often to employ these newer methods and frameworks of thinking, when it is appropriate to do so, and what results can actually be drawn from causal analyses.
In this session, we will hear from four professionals who use causal inference in their day-to-day practice. First, Dr. Candice Johnson will discuss whether certain causal studies are inherently gendered by examining hazards in the workforce in male-dominated fields. Dr. Lucy McGowan will talk about whether interaction effects are feasible, clinically significant, and better than subgroup-specific effects in real-world trials. Dr. Maria DeYoreo will explore inferential approaches to estimate causal effects from a study on the effect of state-funded family planning policies on birth outcomes. Finally, Dr. Lu Wang will discuss applying a causal framework to personalized healthcare, demonstrating how causal inference can support flexible, patient-centered decision-making in routine clinical practice.

Speakers

Lucy D’Agostino McGowan

Associate Professor, Wake Forest University

Lucy D’Agostino McGowan is an associate professor in the Department of Statistical Sciences at Wake Forest University. She received her PhD in Biostatistics from Vanderbilt University and completed her postdoctoral training at Johns Hopkins University Bloomberg School of Public... Read More →

Candice Johnson

Michigan State University

Candice Johnson is Assistant Professor in the Department of Epidemiology and Biostatistics at Michigan State University. She studies how work-related exposures and policies affect the health of workers and their families, with a focus on women and pregnant women in the workforce... Read More →

Maria DeYoreo

RAND

Maria DeYoreo is a senior statistician at RAND. Her substantive interests include health care quality and performance measurement, Medicare Advantage, hospice care, and maternal/child health. Her methodological interests include causal inference and quasi-experimental methods, Bayesian... Read More →

Lu Wang

University of Michigan

Dr. Lu Wang received her PhD in Biostatistics from Harvard University in 2008 and joined the faculty at the University of Michigan in the same year. Her research focuses on statistical methods for evaluating dynamic treatment regimes, personalized health care, nonparametric and semiparametric... Read More →

Chairs/Hosts

Ashley Mullan

Vanderbilt University

Ashley Mullan is a PhD student and research assistant in the Department of Biostatistics at Vanderbilt University. She earned her MS in Statistics from Wake Forest University. Her research interests include both methods development for measurement error and missing data and their... Read More →

Organizers

Jamie Joseph

Henry Ford Health

Dr. Jamie Joseph is a faculty biostatistician in the Department of Public Health Sciences at Henry Ford Health with a joint appointment as an Assistant Professor of Research at Michigan State University. She earned her PhD in Biostatistics from Vanderbilt University in 2024. Currently... Read More →

S213 Abstracts pdf

Tuesday October 6, 2026 15:00 - 16:00 UTC
Zoom Room #2

Invited Session, Technical Statistical Session

Session ID 213

International Day Of Women in Statistics and Data Science