Data Analysis in Medicine and Health using R
eBook - ePub

Data Analysis in Medicine and Health using R

  1. 294 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Data Analysis in Medicine and Health using R

About this book

Data analysis plays a vital role in guiding medical treatment plans, patient care, and the formulation of control and prevention policies in the field of healthcare. In today's era, researchers in these domains require a firm grasp of data, statistical concepts, and programming skills due to the increasing complexity of data. Reproducible analyses and cutting-edge statistical methods are becoming increasingly necessary.

This book, which is both comprehensive and highly practical, addresses these challenges by laying a solid foundation of data and statistical theory for readers. Subsequently, it equips them with practical skills to conduct analyses using the powerful R programming language, widely used by statisticians. The book takes a gentle approach to help readers navigate data and statistical analysis using R, minimizing the learning curve. RStudio is used as the integrated development environment (IDE) for enhanced productivity for readers to run their R codes.

Following a logical sequence commonly applied in medical and health research, the book covers fundamental concepts of data analysis and statistical modeling techniques. It provides readers, including those with limited statistical knowledge and programming skills, with hands-on experience through R programming.

The online version of this book is available on bookdown.org, a publishing platform provided by RStudio, PBC specifically designed to host books written using the "bookdown" package in R. Additionally, all R codes and datasets in this book can be found on the author's GitHub repository.

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Yes, you can access Data Analysis in Medicine and Health using R by Kamarul Imran Musa,Wan Nor Arifin Wan Mansor,Tengku Muhammad Hanis in PDF and/or ePUB format, as well as other popular books in Computer Science & Data Modelling & Design. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover Page
  2. Half-Title Page
  3. Series Page
  4. Title Page
  5. Copyright Page
  6. Dedication Page
  7. Contents
  8. Preface
  9. 1 R, RStudio and RStudio Cloud
  10. 2 R Scripts and R Packages
  11. 3 RStudio Project
  12. 4 Data Visualization
  13. 5 Data Wrangling
  14. 6 Exploratory Data Analysis
  15. 7 Linear Regression
  16. 8 Binary Logistic Regression
  17. 9 Multinomial Logistic Regression
  18. 10 Poisson Regression
  19. 11 Survival Analysis: Kaplan–Meier and Cox Proportional Hazard (PH) Regression
  20. 12 Parametric Survival Analysis
  21. 13 Introduction to Missing Data Analysis
  22. 14 Model Building and Variable Selection
  23. Bibliography
  24. Index