Event sponsored by:
Biostatistics and Bioinformatics
BERD Core
Duke Clinical and Translational Science Institute (CTSI)
School of Medicine (SOM)
Contact:
BERD CoreSpeaker:
David Yanez, Ph.D.
The interpretability and validity of results taken from research studies, both designed experiments or observational study designs, can be adversely impacted by missing data. In this presentation, we introduce mechanisms of how missing data arises and the impacts (e.g., bias) caused by missingness. We discuss commonly used approaches to remedy problems of missing data (e.g., single-step and multiple imputation) and discuss strengths and limitations of these approaches.
This event is being cross-promoted by the NC BERD Consortium, a collaboration of the CTSA-funded BERD cores at UNC-Chapel Hill, Wake Forest University School of Medicine, and Duke University School of Medicine.