Analyzing Health Data in R for SAS Users

Nonfiction, Health & Well Being, Medical, Reference, Biostatistics, Science & Nature, Mathematics, Statistics, Public Health
Cover of the book Analyzing Health Data in R for SAS Users by Monika Maya Wahi, Peter Seebach, CRC Press
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Author: Monika Maya Wahi, Peter Seebach ISBN: 9781351394277
Publisher: CRC Press Publication: November 22, 2017
Imprint: Chapman and Hall/CRC Language: English
Author: Monika Maya Wahi, Peter Seebach
ISBN: 9781351394277
Publisher: CRC Press
Publication: November 22, 2017
Imprint: Chapman and Hall/CRC
Language: English

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
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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:

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