Monika Maya Wahi, Peter Seebach
November 27, 2017
by Chapman and Hall/CRC
Textbook - 320 Pages - 15 Color & 1 B/W Illustrations
ISBN 9781498795883 - CAT# K30343
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Shows how to do a basic health data analysis typically done in SAS in R
A cookbook of R code commonly used in healthcare data analysis is included, along with a generated dataset for practice
Briefer and more focused than similar books
Examples of similar SAS code and R code are presented side by side for comparison
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.
Differences Between SAS and R. Preparing Data for Analysis. Basic Descriptive Analysis. Basic Regression Analysis.
"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