Biostatistics and Computer-based Analysis of Health Data using R

Nonfiction, Science & Nature, Mathematics, Statistics, Computers, Application Software, Business Software
Cover of the book Biostatistics and Computer-based Analysis of Health Data using R by Christophe Lalanne, Mounir Mesbah, Elsevier Science
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Author: Christophe Lalanne, Mounir Mesbah ISBN: 9780081011751
Publisher: Elsevier Science Publication: July 13, 2016
Imprint: ISTE Press - Elsevier Language: English
Author: Christophe Lalanne, Mounir Mesbah
ISBN: 9780081011751
Publisher: Elsevier Science
Publication: July 13, 2016
Imprint: ISTE Press - Elsevier
Language: English

Biostatistics and Computer-Based Analysis of Health Data Using the R Software addresses the concept that many of the actions performed by statistical software comes back to the handling, manipulation, or even transformation of digital data.

It is therefore of primary importance to understand how statistical data is displayed and how it can be exploited by software such as R. In this book, the authors explore basic and variable commands, sample comparisons, analysis of variance, epidemiological studies, and censored data.

With proposed applications and examples of commands following each chapter, this book allows readers to apply advanced statistical concepts to their own data and software.

  • Features useful commands for describing a data table composed made up of quantitative and qualitative variables
  • Includes measures of association encountered in epidemiological studies, odds ratio, relative risk, and prevalence
  • Presents an analysis of censored data, the key main tests associated with the construction of a survival curve (log-rank test or Wilcoxon), and the Cox regression model
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Biostatistics and Computer-Based Analysis of Health Data Using the R Software addresses the concept that many of the actions performed by statistical software comes back to the handling, manipulation, or even transformation of digital data.

It is therefore of primary importance to understand how statistical data is displayed and how it can be exploited by software such as R. In this book, the authors explore basic and variable commands, sample comparisons, analysis of variance, epidemiological studies, and censored data.

With proposed applications and examples of commands following each chapter, this book allows readers to apply advanced statistical concepts to their own data and software.

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