000			01908nam a22002297a 4500
003			CUTN
005			20231005170323.0
008			231005b |||||||| |||| 00| 0 eng d
020			_a9781498795883
041			_aEnglish
082			_223 _a610.285 _bWAH
100			_aWahi, Monika M
245			_aAnalyzing health data in R for SAS users / _cMonika Wahi and Peter Seebach
260			_aBoca Raton : _bCRC Press, _c2018.
300			_axiii, 318 p.: _c15.88 x 2.54 x 23.5 cm.
505			_a1. Differences Between SAS and R. _t2. Preparing Data for Analysis. _t3. Basic Descriptive Analysis. _t4. Basic Regression Analysis.
520			_aAnalyzing 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.
650			_aBio-informatique
650			_aBioinformatics
700			_aSeebach, Peter
942			_2ddc _cBOOKS
999			_c39847 _d39847