Analyzing health data in R for SAS users / Monika Wahi and Peter Seebach

By:

Wahi, Monika M

Contributor(s):

Seebach, Peter

Material type: Text

TextLanguage: English Publication details: Boca Raton : CRC Press, 2018.Description: xiii, 318 p.: 15.88 x 2.54 x 23.5 cmISBN:

9781498795883

Subject(s):

DDC classification:

23 610.285 WAH

Contents:

1. Differences Between SAS and R. 2. Preparing Data for Analysis. 3. Basic Descriptive Analysis. 4. Basic Regression Analysis.

Summary: 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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Holdings
Item type	Current library	Collection	Call number	Status	Date due	Barcode
General Books	CUTN Central Library Medicine, Technology & Management	Non-fiction	610.285 WAH (Browse shelf(Opens below))	Available		47839

1. Differences Between SAS and R.
2. Preparing Data for Analysis.
3. Basic Descriptive Analysis.
4. Basic Regression Analysis.

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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