From Time-dependent Covariates to
Multistate Endpoints
Wrangling Survival Data: R/Medicine 2019 conference
🗓 September 12, 2019
🕗 01:00pm - 05:00pm
📍 Boston, MA
✅ Register
Overview
In this four-hour workshop, I will review basic code for standard
survival analysis, then work through examples for more complex
scenarios. The majority of the focus will be on creating the correct
dataset using tools available in the survival
package. The final
portion of the class will explore the most complex scenario - multistate
data. The format will be a mix of lecture and hands-on exercises.
Learning objectives
- Understand different survival data formats
- Create start/stop data using functions in the
survival
package - Check data for errors
- Create multistate data and perform basic analysis
Is this course for me?
This workshop is targeted at people who work in the medical field with survival data (or who anticipate needing to work with it). A very basic understanding of survival analysis will be helpful, though not required. A basic understanding of R is assumed.
- Have you had to manipulate data prior to running time-to-event analysis?
- Do you anticipate needing to run analyses with time-dependent
covariates or multiple endpoints?
- Even better, have you used the
survival
package?
- Even better, have you used the
- Have you used R with the RStudio Integrated Development Environment (IDE)? Are you familiar with the various “panes” and “tabs”? For instance, can you quickly find all objects in your current global environment, and can you send R code from a source file (.R, .Rmd) to the console?
Schedule
Time | Activity |
---|---|
01:00 - 01:50 | Session 1 (basic analysis, motivation) |
01:50 - 02:00 | Break |
02:00 - 02:50 | Session 2 (intro to tools, examples) |
02:50 - 03:00 | Break |
03:00 - 03:50 | Session 3 (check data, common mistakes) |
03:50 - 04:00 | Break |
04:00 - 04:50 | Session 4 (multistate data) |
04:50 - 05:00 | Wrap-up / Overtime |
Instructor
Beth Atkinson has been a statistician at Mayo Clinic for 29 years and
has worked with Splus then R since starting at Mayo, including
development work on the rpart
package. She has worked extensively with
Terry Therneau, author of the survival
package, and has spent many
hours wrangling data so that it is set up appropriately for
time-to-event analyses. Currently she is working with Terry and Cindy
Crowson on a book focused on time-to-event analyses, which will include
an on-line compendium of detailed examples.
Pre-work
Welcome to the Wrangling Survival Data workshop! I look forward to meeting you in person. Before attending the workshop, please complete the following prework:
-
Sign up for a free RStudio Cloud account at https://rstudio.cloud/ before the workshop. I recommend logging in with an existing Google or GitHub account, if you have one (rather than creating a new account with another password you have to remember).
-
Please bring a laptop that has the following installed:
- A recent version of R (>=3.6.0), which is available for free at https://cloud.r-project.org/
- A recent version of RStudio Desktop (>=1.2), available for free (RStudio Desktop Open Source License)
- The R packages we will use, which you can install by connecting to the internet, opening RStudio, and running at the command line:
install.packages(c("survival", "survminer", "tidyverse", "lubridate", "arsenal", "broom"))
-
Don’t forget your power cord!
On the day of the workshop, I’ll provide you with an RStudio Cloud project that contains all of the course materials. We will use the software listed above only as an important backup should there be problems with the on-site internet connection.
This work is licensed under a Creative Commons Attribution 4.0
International License.