About the Book
Biostatistics is easy to teach poorly. Too often, books focus on methodology with no emphasis on programming and practical implementations. In contrast, books focused on R programming and visualization rarely discuss foundational topics that provide the infrastructure needed by data analysts to make decisions, evaluate analytic tools, and get ready for new and unforeseen challenges. Thus, we are bridging this divide that had no reason to exist in the first place. The book is unapologetic about its focus on Biostatistics, that is Statistics with Biological, Public Health, and Medical applications, though we think that it could be used successfully for large Statistical and Data Science Courses. Data and code can be downloaded here: https://github.com/muschellij2/biostatmethods
About the Authors
Ciprian Crainiceanu, PhD received his doctorate in statistics from Cornell University in 2003 and is a Professor of Biostatistics at Johns Hopkins University. He has taught the Master level Methods in Biostatistics course using and expanding on materials borrowed from Dr. Caffo, who, in turn, distilled materials developed over many years by other Johns Hopkins University Biostatistics faculty. Dr. Crainiceanu is a generalist, who likes to work in many different scientific areas. He has specialized in wearable and implantable technology (WIT) with application to health studies and Neuroimaging, especially in structural magnetic resonance imaging (MRI) and computed tomography (CT) with application to clinical studies. Drs. Crainiceanu and Caffo are the co-founders and co-directors of the Statistical Methods and Applications for Research in Technology ([SMART](http://www.smart-stats.org/)) research group.
Brian Caffo, PhD is a professor in the Department of Biostatistics at the Johns Hopkins Bloomberg School of Public Health. Along with Roger Peng and Jeff Leek, Dr. Caffo created the Data Science Specialization on Coursera. Dr. Caffo is leading expert in statistics and biostatistics and is the recipient of the PECASE award, the highest honor given by the US Government for early career scientists and engineers.
I am an Assistant Scientist in the Department of Biostatistics at Johns Hopkins Bloomberg School of Public Health. I focus on data science, including teaching a few courses and creating a number of R packages, and the analysis of neuroimaging data.