NIH: Office of Disease Prevention

Medicine: Mind The Gap. NIH Seminar Series.

Bridging the Gap Between Evidence and Practice

Medicine: Mind the Gap is a seminar series that explores issues at the intersection of research, evidence, and clinical practice—areas in which conventional wisdom may be contradicted by recent evidence. From the role of advocacy organizations in medical research and policy, to off-label drug use, to the effectiveness of continuing medical education, the seminar series will aim to engage the National Institutes of Health community in thought-provoking discussions to challenge what we think we know and to think critically about our role in today’s research environment.

Upcoming Seminar

Big Data and the Promise and Pitfalls When Applied to Disease Prevention and Promoting Better Health

Philip E. Bourne, Ph.D. External Website Policy
Associate Director for Data Science
National Institutes of Health
Founding Editor in Chief
PLOS Computational Biology

June 13, 2016
1:30–2:30 p.m. Eastern time
Registration, although not required, is encouraged for planning purposes.

*This seminar will be presented as a webinar on the NIH Videocast page.

About the Seminar

Big Data is an overused term, but it does speak to a break from the past in the amount and complexity of data being gathered and analyzed, as well as in the methods applied to that data. How disruptive will Big Data be in the long run to biomedical research and health care? Dr. Bourne will address this question in light of the Big Data to Knowledge (BD2K) initiative and other trans-NIH data science programs.

About Philip E. Bourne, Ph.D.

Philip E. Bourne, Ph.D., is the Associate Director for Data Science (ADDS) at the National Institutes of Health (NIH). In that role, he sets a vision for and oversees Data Science, including the sharing and sustainability of data and tools.

Dr. Bourne’s research focuses on biological and educational outcomes derived from computation and scholarly communication through algorithms, text mining, machine learning, meta-languages, biological databases, and visualization applied to problems in systems pharmacology, evolution, cell signaling, apoptosis, immunology, and scientific dissemination.

Before coming to the NIH, Dr. Bourne was at the University of California, San Diego. He co-founded 4 companies, co-founded and was founding Editor-in-Chief of the open access journal PLOS Computational Biology, and served as a President of the International Society for Computational Biology. Dr. Bourne is an elected fellow of the American Association for the Advancement of Science (AAAS), the International Society for Computational Biology (ISCB), and the American Medical Informatics Association (AMIA). He was awarded the Jim Gray eScience Award (2010), the Benjamin Franklin Award (2009), the Flinders University Convocation Medal for Outstanding Achievement (2004), the Sun Microsystems Convergence Award (2002), and the CONNECT Award for new inventions (1996 & 97).

Upcoming Seminar

Optimizing Inferences Using Principled Missing Data Treatments

Todd D. Little, Ph.D. External Website Policy
Institute for Measurement, Methodology, Analysis, and Policy
Educational Psychology and Leadership
Texas Tech University

June 29, 2016
11:00 a.m.–12:00 noon Eastern time
Registration, although not required, is encouraged for planning purposes.

*This seminar will be presented as a webinar on the NIH Videocast page.

About the Seminar

In this webinar, Dr. Little will highlight the power and utility of modern principled treatments for missing data to optimize inferences. He will discuss the three issues that occur when data go missing and the three mechanisms that give rise to missing data. Dr. Little will also address how modern principled treatments are capable of remedying the otherwise deleterious effects of unplanned missing data. He will emphasize the importance of the missing data modeling plan as a precursor to any data analytic modeling plan. Lastly, Dr. Little will show how experimentally manipulated missing data can increase the validity and reduce the costs of research.

About Todd D. Little, Ph.D.

Todd D. Little, Ph.D., is a Professor and Director of the Research, Evaluation, Measurement, and Statistics program at Texas Tech University and Director of the Institute for Measurement, Methodology, Analysis, and Policy. He is internationally recognized for his quantitative work on various aspects of applied structural equation modeling (e.g., modern missing data treatments, indicator selection, parceling, modeling developmental processes) as well as his substantive developmental research (e.g., action-control processes and motivation, coping, self-regulation). In 2001, Dr. Little was elected to membership in the Society for Multivariate Experimental Psychology, and in 2009, he was elected President of the American Psychological Association’s (APA) Division 5 (Evaluation, Measurement, and Statistics). He founded, organizes, and teaches in the internationally renowned “Stats Camps” (see Dr. Little is a Fellow in the APA, the Association for Psychological Science, and the American Association for the Advancement of Science. In 2013, he received the Cohen Award from the APA’s Division 5 for distinguished contributions to teaching and mentoring. In 2015, he received the inaugural Distinguished Contributions to Mentoring of Developmental Scientists Award from the Society for Research in Child Development. As an interdisciplinary-oriented collaborator, Dr. Little has published with over 340 persons from around the world in over 65 different peer-reviewed journals. His work has garnered over 17,000 citations with an H-index of 67 and an I-10 index of 151. Dr. Little published Longitudinal Structural Equation Modeling in 2013, and he has edited five books related to methodology including the Oxford Handbook of Quantitative Methods and the Guildford Handbook of Developmental Research Methods (with Brett Laursen and Noel Card).