Research Learning Series (RLS): Talk with a Biostatistician Part 1 - Retrospective Analyses
In this Research Learning Series (RLS) webinar, learn from our panel of biostatisticians as they discuss:
- The process by which datasets are constructed and data relationships are formed
- Aggregation and filtering operations by which datasets can be made to answer specific clinical questions
- The limitations of secondary dataset analyses, including confounders, post-hoc statistical tests, and the use of proxy variables due to unmeasured outcomes
- Statistical tests commonly used in secondary dataset analyses
- Research questions best answered by a dataset analysis
Moderators/Panelists
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Kevin McGurk, MD
Assistant Professor
Medical College of Wisconsin Affiliated Hospitals
Dr. McGurk is an assistant professor in the emergency medicine department at the Medical College of Wisconsin. Prior to pursuing medicine, he worked as an elementary school teacher in the D.C. public school system. He received his medical degree from the Virginia Tech Carilion School of Medicine and completed his residency at Cook County Health, where he also served as chief resident. Dr. McGurk's professional interests include medical education, retrospective research, and medical humanities. He is the M3 EM clerkship director and the 2023 recipient of the Joseph C. Carin Excellence in Teaching Award. -
Christine Ramdin, PhD
Faculty
Rutgers New Jersey Medical School
Christine Ramdin, PhD, is a faculty member at the Instructor level at Rutgers New Jersey Medical School Department of Emergency Medicine. She has a PhD in Biomedical Informatics, and has research interests in Addiction Medicine, Medical Toxicology, Pain Medicine, and Stroke. She has published several studies using big data sources such as NHAMCS, HCUP, and NSSATs, and has worked with the NSDUH and TEDs dataset, along with several other local and national datasets. She has experience in conducting big data analyses and utilizing several different types of statistical methods. -
Michael Makutonin
Medical Student
George Washington University School of Medicine and Health Sciences
Michael Makutonin is a fourth-year medical student at the George Washington University School of Medicine and Health Sciences. He has been involved in dataset and data science research throughout his medical school career, starting multi-institution collaborations by drawing on skills he learned as a software engineer and data science bootcamp instructor. Mr. Makutonin's nascent research career has earned him recognition in the field, including research awards and plenaries at national conferences. Mr. Makutonin is passionate about the potential of data science research to inform and solve impactful problems, and continues to mentor others in the field as an officer in the EMRA research committee and a principal investigator at the George Washington University Healing Clinic, among other roles.