Analyzing Health Data in R for SAS Users
Autor Monika Maya Wahi, Peter Seebachen Limba Engleză Hardback – 27 noi 2017
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
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Specificații
ISBN-13: 9781498795883
ISBN-10: 1498795889
Pagini: 318
Ilustrații: 8-page color insert; 51 Tables, black and white; 15 Illustrations, color; 1 Illustrations, black and white
Dimensiuni: 156 x 234 x 25 mm
Greutate: 0.57 kg
Ediția:1
Editura: CRC Press
Colecția Chapman and Hall/CRC
ISBN-10: 1498795889
Pagini: 318
Ilustrații: 8-page color insert; 51 Tables, black and white; 15 Illustrations, color; 1 Illustrations, black and white
Dimensiuni: 156 x 234 x 25 mm
Greutate: 0.57 kg
Ediția:1
Editura: CRC Press
Colecția Chapman and Hall/CRC
Cuprins
Differences Between SAS and R. Preparing Data for Analysis. Basic Descriptive Analysis. Basic Regression Analysis.
Notă biografică
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.
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.
Recenzii
"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
Descriere
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.