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List of contents
Differences Between SAS and R. Preparing Data for Analysis. Basic Descriptive Analysis. Basic Regression Analysis.
About the author
Monika M. Wahi, MPH, CPH is an experienced epidemiologist with multiple peer-reviewed articles and book chapters on many public health subjects. Her focus is on applying informatics methods to the practice of epidemiology, as well as teaching public health and biostatistics. She serves as a lecturer at Laboure College in Milton, Massachusetts and is Chief Science Officer of Vasanta Health Science.
Peter Seebach has over 25 years of experience with programming languages, ranging from developing open source projects to working on language standards committees. He currently works as a Senior devOps Engineer at Markley Cloud Services. His previous publications include a number of technical articles and the book Beginning Portable Shell Scripting.
Summary
This book discusses how to do routine health data analysis, typically done in SAS, in R. It assumes that the audience has some experience in this area. Many SAS users want to try R, but R developers have not focused on health data analysis cookbooks. This book will allow them to add R to their analytic skills toolbox.
Additional text
"R is an increasingly popular programming in statistics and data science. This well-presented and timely book builds a critical bridge between SAS and R, which is particularly appropriate for students and researchers with knowledge and experiencing in using SAS language to gain programming proficiency in R language. I highly recommend this very insightful book to statisticians, data scientists, social scientists, psychologists, biologists, public health researchers and practitioners, and clinicians who are familiar with SAS to harness the magnificent power of R. I would use this book as a major reference book for a biostatistics course on R."~Tianhua Niu, Tulane University School of Medicine
