Title: Fostering Inclusiveness in Big Data: Changing the Normative Process for Selecting Covariates in Statistical Models

Presented by Stephanie Cook
New York University James Weldon Johnson Professor
Assistant Professor of Social and Behavioral Sciences
Assistant Professor of Biostatistics
Director, Attachment and Health Disparities Research Lab

Abstract: In observational and/or epidemiological research, we often adjust for a host of socio-demographic variables to clarify the influence of a predictor on an outcome. However, we rarely utilize all possible covariates. Instead, we use what is available or the normative variables we have been taught to include. To be more inclusive of underrepresented communities, we have to start making the invisible visible by showing representation in our statistical analyses. Thus, in this presentation, I will first discuss how to be more inclusive in the ways in which we select and utilize covariates in statistical analyses. I will then show examples of this from my work. Lastly, I will pivot a bit and talk about how we must also incorporate such inclusivity and representation in analyses into our statistical teaching.

A seminar tea will be held at 11:00 a.m. in University Office Plaza, Room 116. All are Welcome.