Analyzing Health Data in R for SAS Users

Monika Maya Wahi (Laboure College, Milton, MA USA), Peter Seebach

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English

Chapman & Hall/CRC
18 December 2020

Epidemiology & medical statistics; Probability & statistics; Mathematical & statistical software

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 R

Demonstrates descriptive statistics as well as linear and logistic regression

Provides exercise questions and answers at the end of each chapter

Uses examples from the publicly available dataset, Behavioral Risk Factor Surveillance System (BRFSS) 2014 data

Guides the reader on producing a health analysis that could be published as a research report

Gives an example of hypothesis-driven data analysis

Provides examples of plots with a color insert

By: Monika Maya Wahi (Laboure College Milton MA USA), Peter Seebach
Imprint: Chapman & Hall/CRC
Country of Publication: United Kingdom
Dimensions: Height: 234mm, Width: 156mm,
Weight: 458g
ISBN: 9780367735531
ISBN 10: 0367735539
Pages: 320
Publication Date: 18 December 2020
Audience: College/higher education , Professional and scholarly , Primary , Undergraduate
Format: Paperback
Publisher's Status: Active

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.

Reviews for Analyzing Health Data in R for SAS Users

"""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"