Video: knitr, R Markdown, and R Studio: Introduction to Reproducible Analysis

This post presents the video of a talk that I presented in July 2012 at Melbourne R Users on using knitr, R Markdown, and R Studio to perform reproducible analysis. I also provide links to a github repository where the R markdown examples can be examined and the slides can be downloaded.

Converting Sweave LaTeX to knitr LaTeX: A case study

The following post documents the steps I needed to take in order to convert a project using Sweave LaTeX into one using knitr LaTeX.

How to Convert Sweave LaTeX to knitr R Markdown: Winter Olympic Medals Example

The following post shows how to manually convert a Sweave LaTeX document into a knitr R Markdown document. The post (1) reviews many of the required changes; (2) provides an example of a document converted to R Markdown format based on an analysis of Winter Olympic Medal data up to and including 2006; and (3) discusses the pros and cons of LaTeX and Markdown for performing analyses.

Example Reproducible Report using R Markdown: Analysis of California Schools Test Data

This is a quick set of analyses of the California Test Score dataset. The post was produced using R Markdown in RStudio 0.96. The main purpose of this post is to provide a case study of using R Markdown to prepare a quick reproducible report. It provides examples of using plots, output, in-line R code, and markdown. The post is designed to be read along side the R Markdown source code, which is available as a gist on github.

Getting Started with R Markdown, knitr, and Rstudio 0.96

This post examines the features of R Markdown using knitr in Rstudio 0.96. This combination of tools provides an exciting improvement in usability for reproducible analysis. Specifically, this post (1) discusses getting started with R Markdown and knitr in Rstudio 0.96; (2) provides a basic example of producing console output and plots using R Markdown; (3) highlights several code chunk options such as caching and controlling how input and output is displayed; (4) demonstrates use of standard Markdown notation as well as the extended features of formulas and tables; and (5) discusses the implications of R Markdown. This post was produced with R Markdown. The source code is available here as a gist. The post may be most useful if the source code and displayed post are viewed side by side. In some instances, I include a copy of the R Markdown in the displayed HTML, but most of the time I assume you are reading the source and post side by side.

Getting Started with Sweave: R, LaTeX, Eclipse, StatET, & TeXlipse

Being able to press a single button that runs all your statistical analyses and integrates the output into your final report is a beautiful thing. If you have not already heard, this is what Sweave can do for you. However, getting your computer to run Sweave can be a little bit fiddly. Thus, this post: (1) sets out the benefits of Sweave; (2) sets out how to install and configure R, Sweave, and Eclipse on Windows; (3) lists resources for people wanting to learn more about how to use LaTeX and Sweave; and (4) lists some specific resources relevant to researchers in psychology wanting to use these tools.

Comments on "Data Intensive Scientific Discovery"

An interesting book has been published free online on the future of the scientific method and the role of computing, software, and information systems: Data Intensive Scientific Discovery
The ideas link in with the concerns of myself and others with reproducible research, data sharing, data analysis, and open publishing.

Introduction to SPSS Syntax | Advice for Conducting Reproducible Research

This post provides an overview of SPSS syntax for researchers using SPSS. It sets out (1) why it is important to use syntax, (2) tips on how to use and learn syntax, (3) tips on dealing with errors; 4) tips on organising your syntax, (5) additional resources to learn more, and (6) where to go after you have reached the limits of SPSS syntax.