Observational Study Overview and Design: An Instrumental Variable Based Approach
Observational Study aims to draw inference about the possible effect of a treatment on subjects from an empirical comparison of treated and controlled groups, which is widely used in all kinds of healthcare and medical research when clinical trials are not applicable in practice. In this presentation, I will focus on the overview of Observational Study in terms of conceptual definition, study design, and biases adjustment. An instrumental variable based approach will be mainly introduced for its superiority in statistical inference to avoid the strong “no unmeasured confounders” assumption in observational studies.
Dr. Pan Wu is the Senior Biostatistician for the Value Institute at the Christiana Care Health System. He received his PhD in Statistics from the Department of Biostatistics and Computational Biology at the University of Rochester in 2013. His research interests include Causal Inference, Medication Analysis, Longitudinal Study with Missing Data, latent mixture models, data mining, and high-dimensional variable selection.
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.
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Contact Sarahfaye Dolman at sarahfaye.f.dolman@christianacare.org with any questions.