๐”– Scriptorium
โœฆ   LIBER   โœฆ

๐Ÿ“

Analyzing Health Data in R for SAS Users

โœ Scribed by Monika Maya Wahi, Peter Seebach


Publisher
Chapman and Hall/CRC;Taylor & Francis Group
Year
2018
Tongue
English
Leaves
319
Edition
1
Category
Library

โฌ‡  Acquire This Volume

No coin nor oath required. For personal study only.

โœฆ 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

โœฆ Table of Contents


Content: Differences Between SAS and R. Preparing Data for Analysis. Basic Descriptive Analysis. Basic Regression Analysis.

โœฆ Subjects


SAS (Computer file);Bioinformatics.;Medical informatics.;R (Computer program language)


๐Ÿ“œ SIMILAR VOLUMES


Statistical Analytics for Health Data Sc
โœ Jeffrey Wilson, Ding-Geng Chen, Karl E. Peace ๐Ÿ“‚ Library ๐Ÿ“… 2023 ๐Ÿ› CRC Press/Chapman & Hall ๐ŸŒ English

<p><span>This book aims to compile typical fundamental-to-advanced statistical methods to be used for health data sciences. Although the book promotes applications to health and health-related data, the models in the book can be used to analyze any kind of data. The data are analyzed with the common

SAS for R users : a book for budding dat
โœ Ohri, Ajay ๐Ÿ“‚ Library ๐Ÿ“… 2020 ๐Ÿ› John Wiley & Sons ๐ŸŒ English

"This book will enable students and practitioners to easily switch from R to SAS and vice versa. R has better statistical and graphical tools, while SAS has faster data handling, is easier to learn and is the leading corporate software in analytics. This book builds a cross-functional framework for

R for SAS and SPSS Users
โœ Robert A. Muenchen ๐Ÿ“‚ Library ๐Ÿ“… 2008 ๐Ÿ› Springer ๐ŸŒ English

<P>R is a powerful and free software system for data analysis and graphics, with over 1,200 add-on packages available. This book introduces R using SAS and SPSS terms with which you are already familiar. It demonstrates which of the add-on packages are most like SAS and SPSS and compares them to Rะฒะ‚

R for SAS and SPSS Users
โœ Robert A. Muenchen (auth.) ๐Ÿ“‚ Library ๐Ÿ“… 2009 ๐Ÿ› Springer New York ๐ŸŒ English

R is a powerful and free software system for data analysis and graphics, with over 1,200 add-on packages available. This book introduces R using SAS and SPSS terms with which you are already familiar. It demonstrates which of the add-on packages are most like SAS and SPSS and compares them to Rโ€™s bu