Data Analysis in Medicine and Health using R

1. Auflage 2023
ISBN: 978-1-03-228414-9
Verlag: Taylor & Francis Ltd

Buch, Englisch, 310 Seiten, Format (B × H): 234 mm x 156 mm, Gewicht: 476 g

Reihe: Analytics and AI for Healthcare

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.

Zielgruppe

General

Autoren/Hrsg.

Musa, Kamarul Imran

Hanis, Tengku Muhammad

Mansor, Wan Nor Arifin Wan

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizinische Mathematik & Informatik
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Automatische Datenerfassung, Datenanalyse
• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Spiele-Programmierung, Rendering, Animation
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Datenbankdesign & Datenbanktheorie
• Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion Informationsarchitektur

Inhaltsverzeichnis

1. R, RStudio and RStudio Cloud 2. R Scripts and R Packages 3. RStudio Project 4. Data Visualization 5. Data Wrangling 6. Exploratory Data Analysis 7. Linear Regression 8. Binary Logistic Regression 9. Multinomial Logistic Regression 10. Poisson Regression 11. Survival Analysis: Kaplan–Meier and Cox Proportional Hazard (PH) Regression 12. Parametric Survival Analysis 13. Introduction to Missing Data Analysis 14. Model Building and Variable Selection

Über Autor(innen)

Kamarul Imran Musa is an associate professor and medical epidemiologist at the School of Medical Sciences, Universiti Sains Malaysia. He is a registered public health physician with the Malaysia National Specialist Registry and a Fellow of the American College of Epidemiology (FACE). He is also a core member of the Malaysia R User group and conducts regular workshops on data and statistical analysis at the national level.

Wan Nor Arifin is a senior lecturer at the Biostatistics and Research Methodology Unit, School of Medical Sciences, Universiti Sains Malaysia. His research is mainly in validating measurement tools and machine learning, especially for use in clinical and public health settings. He is also a core member of the Malaysia R User group. He uses the R statistical programming language on a daily basis and promotes its use in medical research.

Tengku Muhammad Hanis is a PhD student at the School of Medical Sciences, Universiti Sains Malaysia. He holds a master's degree in medical statistics. His interests lie in the application of medical statistics and machine learning in medicine. He has run several workshops on bibliometric analysis, systematic reviews, and meta-analysis. He is passionate about R and always excited about its potential in medical and health research.