This book covers the aspects of R most often used by statistical analysts. Incorporating the use of RStudio and the latest R packages, this second edition offers new chapters on simulation, special topics, and case studies. It reorganizes and enhances the chapters on data input and output, data management, statistical and mathematical functions, programming, high-level graphics plots, and the customization of plots. It also provides a detailed discussion of the philosophy and use of the knitr and markdown packages for R.

Nicholas J. Horton is a professor of statistics at Amherst College. His research interests include longitudinal regression models and missing data methods, with applications in psychiatric epidemiology and substance abuse research.

Ken Kleinman is an associate professor in the Department of Population Medicine at Harvard Medical School. His research deals with clustered data analysis, surveillance, and epidemiological applications in projects ranging from vaccine and bioterrorism surveillance to observational epidemiology to individual-, practice-, and community-randomized interventions.

Data Input and Output. Data Management. Statistical and Mathematical Functions. Programming and Operating System Interface. Common Statistical Procedures. Linear Regression and ANOVA. Regression Generalizations and Modeling. A Graphical Compendium. Graphical Options and Configuration. Simulation. Special Topics. Case Studies. Appendices.