Biostatistics Short Course: An Introduction to the Analysis of Incomplete Data
Missing data is a common complication in applied research. Although most researchers and scientists tend to ignore this problem, research has proven that correcting this issue is important. Biased results and inefficient estimates are just some of the risks of having incomplete data. In this course, we will introduce vocabulary on incomplete data and present problems and solutions. We will provide guidance on implementing mitigation procedures including software options. This course is intended for researchers and quantitative scientists with a basic knowledge of statistical inference.
Ofer Harel, PhD, is the interim dean of the College of Liberal Arts and Sciences at the University of Connecticut and a professor in the Department of Statistics. Harel received his doctorate in statistics in 2003 from the Department of Statistics at Pennsylvania State University; where he developed his methodological expertise in the areas of missing data techniques, diagnostic tests, longitudinal studies, Bayesian methods, sampling techniques, mixture models, latent class analysis, and statistical consulting. Harel received his postdoctoral training at the University of Washington, Department of Biostatistics, where he worked for the Health Services Research & Development (HSR&D) Center of Excellence, VA Puget Sound Healthcare System, and the National Alzheimer’s Coordinating Center (NACC). He is a member of the National Academy of Science, Engineering and Medicine’s Committee on Applied and Theoretical Statistics. Harel was a member of the (now restructured) Biostatistical Methods and Research Design (BMRD) Study Section at the National Institute of Health and was appointed to the Bureau of Labor Statistics Technical Advisory Committee (BLSTAC) at the U.S. Bureau of Labor Statistics among many national elected and appointed positions.