7th February 15:00 - 16:00
Online - you will receive an email link before the event.
Rameela Raman, Ph.D., is an Associate Professor of Biostatistics at Vanderbilt University, Tennessee, USA. She has published more than 100 peer-reviewed articles and has been collaborating for over a decade as the lead statistician with the Vanderbilt Center of Excellence for Children in State Custody, an academic partner to the Tennessee Department of Children’s Services. In this role, she works with a team including child psychologists, epidemiologists, biostatisticians and substantive experts to formulate a question that is relevant to their field, to place the results in context and communicate the results to policymakers. Much of her work involves critically analyzing current practices and evaluating effectiveness of interventions to guide research, policy, and advocacy to improve the lives of children in or at-risk of coming into state custody. Her research interests include leveraging multiple sources of data to incorporate social determinants to study outcomes of interest. Dr. Raman graduated with a MA and PhD in Biostatistics from the State University of New York at Buffalo.
Administrative data sources provide a wealth of information and are a valuable resource for research. However, they are limited in the amount of information they capture and may not provide a comprehensive picture. Recently, integrating data from other sources (e.g., neighborhood-level socioeconomic characteristics from the United States Census) and linking them to child welfare administrative data has been shown to be an approach to address the limitations. In this talk, Rameela will present examples of real-world policy-relevant research projects from my work with a US child welfare system to motivate a discussion on the advantages and challenges of using linked data. Rameela will also touch on the types of research questions that can be addressed through linked data and demonstrate interactive ways of presenting and communicating analysis results.
