CHOP R 101: Intro to R for Clinical Data

A gentle introduction to data science for healthcare professionals and clinical researchers.

Arcus Data Education https://education.arcus.chop.edu/ (Children’s Hospital of Philadelphia)https://www.chop.edu

Welcome!

This is the website for the short course Introduction to R for Clinical Data organized by the CHOP R User Group.

You’ll learn about R Markdown, a framework for reproducible data science, and how to perform essential data science tasks such as data import, visualization, transformation, and communication.

For the best experience during the workshop, we suggest the following (none of the below are absolutely necessary!):

The entire course will be recorded and made available to CHOP R User Group members for replay. To protect the privacy of participants, no breakouts, video feeds, or chats will be recorded. We also request that you refrain from recording or screen-grabbing any part of the course.

Pre-work

Essential

After the course

Watch a replay!

If you’d like a refresher, we suggest that you download the course materials to your computer and follow along with a replay of the workshop.

Make sure you have both R and RStudio installed (see above).

To download the materials from the course, go to the GitHub repository, and click the green button labeled “Code” to download the repository as a .ZIP file. Unzip that file. Inside of the folder that was created by unzipping the file, double click intro-to-r-for-clinicians.Rproj to open a new RStudio session. You should be able to see the exercises folder (among other things) in the Files pane.

Now install all the packages we used in the training environment. To do so, run the following command in the Console:

install.packages(c(
  "tidyverse",
  "rmarkdown"
))

Join the CHOP R User Group!

If you haven’t already done so, please consider joining the CHOP R User Group, which is open to anyone with a CHOP or Penn email address. Click here to sign up!

We won’t spam you, we promise, but you’ll get invites to user group meetings (semi-regular, about once a month or so) about all sorts of R-related topics, plus an invite to the Slack channel, where you can chat with folks (and ask questions) about R.

Resources

Acknowledgments

This course is based closely on material developed by Stephan Kadauke. You can see the materials for Stephan’s original course, including recordings of the entire workshop, at his course website: https://skadauke.github.io/intro-to-r-for-clinicians-chop/. Thank you, Stephan, for developing such amazing materials and for sharing them under a Creative Commons license!

This site is built using the distill package.