Analyzing Health Data in R for SAS Users

Analyzing Health Data in R for SAS Users is aimed at helping health data analysts who use SAS accomplish some of the same tasks in R. It is targeted to public health students and professionals who have a background in biostatistics and SAS software, but are new to R. For professors, it is useful as a textbook for a descriptive or regression modeling class, as it uses a publicly-available dataset for examples, and provides exercises at the end of each chapter. For students and public health professionals, not only is it a gentle introduction to R, but it can serve as a guide to developing the results for a research report using R software.Features:Gives examples in both SAS and RDemonstrates descriptive statistics as well as linear and logistic regressionProvides exercise questions and answers at the end of each chapterUses examples from the publicly available dataset, Behavioral Risk Factor Surveillance System (BRFSS) 2014 dataGuides the reader on producing a health analysis that could be published as a research reportGives an example of hypothesis-driven data analysisProvides examples of plots with a color insert

Differences Between SAS and R. Preparing Data for Analysis. Basic Descriptive Analysis. Basic Regression Analysis.

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.