Analyzing Health Data in R for SAS Users

Monika Maya Wahi

ISBN 10: 0367735539 / ISBN 13: 9780367735531

Published by CRC Press Dez 2020, 2020

About this Item

Neuware - 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.

Seller Inventory # 9780367735531

Bibliographic Details

• Title: Analyzing Health Data in R for SAS Users
• Publisher: CRC Press Dez 2020
• Publication Date: 2020
• Language: English
• ISBN 10: 0367735539
• ISBN 13: 9780367735531
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 234W x 156H x 0D millimeters 234 millimeters width by 156 millimeters height by 0 millimeters depth
• Weight: 590 grams

About this title

Synopsis

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

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.