R is a language and free software environment for statistical computing and graphics. It compiles and runs on a variety of UNIX platforms, Windows, and MacOS. It is similar to the S language and environment – in fact, much code written in S will run unaltered in R. The R environment is an integrated suite of software facilities for data manipulation, calculation and graphical display. You can learn more about R from the R Project website.
How Can I Get R?
R is open source and freely downloadable from the R website. To download, go to the R Project CRAN web page and search for the location nearest you. You may also be interested in the following R packages:
- epitools: R package for epidemiologic data and graphics
Help with R
- RStudio Training Resources “RStudio is a company dedicated to providing software, education, and services for the R statistical computing environment.”
- “twotorials” by Anthony Damico – A list of 91 two minute tutorials on how to do various things in the R environment. “how to do stuff in r. two minutes or less.”
- Try R by Cde School – Free online course with 7 chapters: R Syntax, Vectors, Matrices, Summary Statistics, Factors, Data Frames, and Working with Real-World Data.
- r-fiddle.org – Online playground for R code.
- R for Public Health Blog – The author created the R for Public Health blog for public health researchers who are used to Stata or SAS to begin using R. She takes into account the unique qualities of public health data and attempts to address the specific data management and analysis needs of the public health world.
- Valence Analytics – JHU Public Health – Biostatistics student’s explanations’ on how to use R.
R for Epidemiology
- Medepi.com – Medical Epidemiology – Tomás Aragón, MD, DrPH – “The purpose of this not-for-profit site is to share public health concepts and methods in diverse areas, including epidemiology and control of infectious diseases, emergency preparedness and response, epidemiologic methods and computing, community and population health, health leadership and management, complexity sciences in health, and multi-criteria decision making. These topics are based on my experience, expertise, and interests. In all these areas I am an enthusiastic student with much to discover and learn.”
- Applied Epidemiology Using R – An Open Access Book by Tomás Aragón
- epitools: R package for
- A short introduction to R for Epidemiology – Michael Hills, Martyn Plummer, Bendix Carstensen
Anaylsis of epidemiological data using R and Epicalc – Virasakdi Chongsuvivatwong, Epidemiology Unit, Prince of Sangkla University, Thailand
For the R Surveillance Package
R training from BioSense 2.0
- R Training for BioSense 2.0 – 9/7/12
- Visualizations in R – 1/22/13