From SPSS to R: How to Make Your Statistical Analysis Reproducible

Comfortable/aware of how to run your stats in SPSS? Curious to learn how to run them in R? You've come to the right place.

In part 1 of this course, we will learn to:

• Download and navigate R.
• Work with R markdown documents.
• Conduct our trusty SPSS analysis through R.

In part 2 of this course, we will learn to:

• Upload your own data to R.
• Create a data tidying script.
• Learn how to save your tidied data (in case you want to transfer analysis to other software/supervisors).
• A reminder of our analyses.
• Learn how to create APA ready analysis outputs - no more copy and pasting our results!

The material in this repo was developed and curated by Rhys Davies. All material collected here is free to use but is covered by a License: license

R Setting Up

You can either run the code on your own machine or through Posit (RStudio Online IDE) or if you are part of the University of Edinburgh through Noteable. Below are the instructions for setting up.

On Posit

1. Go to https://posit.cloud/
2. Signup either via Gmail or GitHub
3. Go on New Project
4. New Project from Git Repository
5. Copy and Paste this repository URL https://github.com/DCS-training/From-SPSS-to-R-How-to-Make-Your-Statistical-Analysis-Reproducible as the Repository URL
6. The Project directory name will filled in automatically
7. Navigate to the rmd file you want to explore

Locally

• R and RStudio are separate downloads and installations. R is the underlying statistical computing environment, but using R alone is no fun. RStudio is a graphical integrated development environment (IDE) that makes using R much easier and more interactive. You need to install R before you install RStudio. After installing both programs, you will need to install some specific R packages within RStudio. Follow the instructions below for your operating system, and then follow the instructions to install the needed packages(below)

Windows

• If you already have R and RStudio installed

  • Open RStudio, and click on "Help" > "Check for updates". If a new version is available, quit RStudio, and download the latest version for RStudio.
  • To check which version of R you are using, start RStudio and the first thing that appears in the console indicates the version of R you are running. Alternatively, you can type sessionInfo(), which will also display which version of R you are running. Go on the CRAN website and check whether a more recent version is available. If so, please download and install it. You can check here for more information on how to remove old versions from your system if you wish to do so.

• If you don't have R and RStudio installed

  • Download R from the CRAN website.
  • Run the .exe file that was just downloaded
  • Go to the RStudio download page
  • Under Installers select RStudio x.yy.zzz - Windows Vista/7/8/10 (where x, y, and z represent version numbers)
  • Double click the file to install it
  • Once it's installed, open RStudio to make sure it works and you don't get any error messages.

macOS

• If you already have R and RStudio installed

  • Open RStudio, and click on "Help" > "Check for updates". If a new version is available, quit RStudio, and download the latest version for RStudio.
  • To check the version of R you are using, start RStudio and the first thing that appears on the terminal indicates the version of R you are running. Alternatively, you can type sessionInfo(), which will also display which version of R you are running. Go on the CRAN website and check whether a more recent version is available. If so, please download and install it.

• If you don't have R and RStudio installed

  • Download R from the CRAN website.
  • Select the .pkg file for the latest R version
  • Double-click on the downloaded file to install R
  • It is also a good idea to install XQuartz (needed by some packages)
  • Go to the RStudio download page
  • Under Installers select RStudio x.yy.zzz - Mac OS X 10.6+ (64-bit) (where x, y, and z represent version numbers)
  • Double-click the file to install RStudio
  • Once it's installed, open RStudio to make sure it works and you don't get any error messages.

Linux

• Follow the instructions for your distribution from CRAN, they provide information to get the most recent version of R for common distributions. For most distributions, you could use your package manager (e.g., for Debian/Ubuntu run sudo apt-get install r-base, and for Fedora sudo yum install R), but we don't recommend this approach as the versions provided by this are usually out of date. In any case, make sure you have at least R 3.5.1.
• Go to the RStudio download page
• Under Installers select the version that matches your distribution, and install it with your preferred method (e.g., with Debian/Ubuntu sudo dpkg -i rstudio-x.yy.zzz-amd64.deb at the terminal).
• Once it's installed, open RStudio to make sure it works and you don't get any error messages.

Once you have R and R Studio installed, open R Studio

1. Go to File>New Project> Version Control >Git
2. Enter the Repository URL https://github.com/DCS-training/From-SPSS-to-R-How-to-Make-Your-Statistical-Analysis-Reproducible
3. Select the Name for the directory project and where to save it
4. Press Create Project

On Noteable

1. Go to https://noteable.edina.ac.uk/login
2. Login with your EASE credentials
3. Select RStudio as a personal notebook server and press start
4. Go to File >New Project>Version Control>Git
5. Copy and Paste this repository URL https://github.com/DCS-training/From-SPSS-to-R-How-to-Make-Your-Statistical-Analysis-Reproducible as the Repository URL
6. The Project directory name will filled in automatically but you can change it if you want your folder in Notable to have a different name
7. Decide where to locate the folder. By default, it will locate it in your home directory
8. Press Create Project