Propensity Score Matching for Estimating Treatment Effects
Propensity Scores matching is used to adjust for selection bias in non-randomized studies to compare the effectiveness of interventions when there are significant baseline differences between the intervention groups. This presentation will discuss how to estimate the propensity score, form matched sets of subjects, assess the similarity of baseline factors between intervention groups, and estimate the effect of treatment in matched samples.
Dr. Zugui Zhang is the lead Biostatistician for the Value Institute of Christiana Care Health System and research assistant professor at Thomas Jefferson University. He has a broad background in health outcomes research, public health, epidemiology, and biostatistics. He has worked extensively on large international and national, multi-center, randomized clinical trials and observational studies.
The Innovative Discoveries Series, sponsored by the Delaware Clinical & Translational Science ACCEL program and the Christiana Care Value Institute, features informal presentations on topics relevant to current research and healthcare practice, led by knowledgeable and experienced presenters. There are offerings for researchers, healthcare providers, and community members of varying levels of experience.
These free talks are held Fridays at noon at Christiana Hospital but can be viewed from your home or office computer. Earn CMEs by participating in-person or online. Lunch is served and all are welcome to attend.
To see the full calendar of events, visit the Value Institute Events page or the ACCEL website, or subscribe to the ID Series mailing list.
Contact Sarahfaye Dolman at sarahfaye.f.dolman@christianacare.org with any questions.