Reproducible Research with R and R Studio, 2nd Edition

All the Tools for Gathering and Analyzing Data and Presenting Results

Reproducible Research with R and RStudio, Second Edition brings together the skills and tools needed for doing and presenting computational research. Using straightforward examples, the book takes you through an entire reproducible research workflow. This practical workflow enables you to gather and analyze data as well as dynamically present results in print and on the web.

New to the Second Edition

• The rmarkdown package that allows you to create reproducible research documents in PDF, HTML, and Microsoft Word formats using the simple and intuitive Markdown syntax
• Improvements to RStudio’s interface and capabilities, such as its new tools for handling R Markdown documents
• Expanded knitr R code chunk capabilities
• The kable function in the knitr package and the texreg package for dynamically creating tables to present your data and statistical results
• An improved discussion of file organization, enabling you to take full advantage of relative file paths so that your documents are more easily reproducible across computers and systems
• The dplyr, magrittr, and tidyr packages for fast data manipulation
• Numerous modifications to R syntax in user-created packages
• Changes to GitHub’s and Dropbox’s interfaces

Create Dynamic and Highly Reproducible Research

This updated book provides all the tools to combine your research with the presentation of your findings. It saves you time searching for information so that you can spend more time actually addressing your research questions. Supplementary files used for the examples and a reproducible research project are available on the author’s website.

Table of Contents

Part I Getting Started
Chapter 1 Introducing Reproducible Research
Chapter 2 Getting Started with Reproducible Research
Chapter 3 Getting Started with R, RStudio, and knitr/rmarkdown
Chapter 4 Getting Started with File Management

Part II Data Gathering and Storage
Chapter 5 Storing, Collaborating, Accessing Files, and Versioning
Chapter 6 Gathering Data with R
Chapter 7 Preparing Data for Analysis

Part III Analysis and Results
Chapter 8 Statistical Modeling and knitr
Chapter 9 Showing Results with Tables
Chapter 10 Showing Results with Figures

Part IV Presentation Documents 213
Chapter 11 Presenting with knitr/LaTeX
Chapter 12 Large knitr/LaTeX Documents: Theses, Books, and Batch Reports
Chapter 13 Presenting on the Web and Other Formats with R Mark down
Chapter 14 Conclusion