There are several excellent resources available for learning biostatistics using R. Here are some highly recommended options:
Biostatistical Design and Analysis Using R: A Practical Guide
This book draws upon the popularity and free availability of R to couple the theory and practice of biostatistics into a single treatment, so as to provide a textbook for biologists learning statistics, R, or both. An abridged description of biostatistical principles and analysis sequence keys are combined together with worked examples of the practical use of R into a complete practical guide to designing and analyzing real biological research. Link
Biostatistics: A Foundation for Analysis in the Health Sciences
Biostatistics: A Foundation for Analysis in the Health Sciences by Wayne W. Daniel and Chad L. Cross: This comprehensive textbook provides a solid foundation in biostatistics and covers a wide range of topics. It includes numerous examples and exercises using R, making it a valuable resource for learning biostatistics with R.
Introduction to Biostatistics
“Introduction to Biostatistics” by Robert R. Sokal and F. James Rohlf: Another popular textbook that covers the fundamentals of biostatistics. While it doesn’t focus specifically on R, it provides a solid understanding of the concepts, and you can apply the techniques using R on your own.
Biostatistics with R: An Introduction to Statistics Through Biological Data
“Biostatistics with R: An Introduction to Statistics Through Biological Data” by Babak Shahbaba: This book specifically integrates the use of R for biostatistics. It covers a range of statistical techniques commonly used in the field and provides hands-on examples and exercises using R.
Biostatistics: A Computing Approach
“Biostatistics: A Computing Approach” by Stewart Anderson: This book emphasizes the practical application of biostatistical concepts using R. It covers essential topics and includes R code and exercises to reinforce learning.
Online courses
Websites like Coursera, edX, and DataCamp offer online courses on biostatistics and R programming. For example, Coursera offers the course “Biostatistics in Public Health” by Johns Hopkins University, which includes R programming assignments. DataCamp provides courses like “Biostatistics in R: Clinical Trial Applications” and “Analyzing Biomedical Data in R” that focus specifically on biostatistics with R.
Online tutorials and resources
Websites like R-bloggers and the official R documentation (https://www.r-project.org) provide a wealth of tutorials, examples, and documentation on using R for biostatistics. You can find specific articles and blog posts related to biostatistics, as well as R packages tailored for the field.
Remember that practicing with real-world datasets and solving problems related to biostatistics will enhance your understanding and proficiency. It’s a good idea to combine learning resources with hands-on practice using relevant datasets to gain practical experience.