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Introduction to Survival Analysis using R

Dates: Tuesday 10 - Thursday 12 December 2024

(Optional ‘Introduction to R’ day on Monday 9 December) 

Registration is now open. Please see the link at the bottom of the page. This course is only open to Oxford staff and students.

Maximum capacity: 25

Venue: Main meeting room, Richard Doll Building, Old Road Campus, Oxford

Course directors: Stephanie Ross, Andrew Browne, Jennifer Carter

Introduction

Introduction to Survival Analysis using R aims to give students an understanding of the statistical methods used to analyse time-to-event data using practical examples in R.

Who is this course for?

The course is intended for those who wish to analyse and understand survival data. This is the companion and follow-on course from our Introduction to Epidemiology and Practical Statistics for Epidemiology using R short courses. Students are required to have prior knowledge of statistics, including the use of linear and logistic regression models. No prior experience with statistical software is required and there is an optional one day Introduction to R course for those who require further training in R.

Course content

During the three day in-person survival course, participants will be introduced to:

  • the concept of survival data
  • creating Kaplan-Meier plots and implementing the log-rank test
  • Cox regression models and testing the proportional hazards assumptions
  • extensions of the Cox Model
  • modelling Survival data for health economics models

All course content employs the freely-available statistical programme R. The teaching on this course is a combination of lectures, hands-on practicals and online quizzes.

 

During the optional one-day introduction to R for those who need it, participants will learn how to:

  • install and understand how to use R and RStudio
  • install and load necessary packages fo
  • read data into R and manipulate it
  • calculate summary statistics for variables in R
  • construct linear and logistic regression models in R.

Outcomes

By the end of the course, students will be able to:

  • produce and interpret graphical displays appropriate for survival analysis
  • analyse survival data and interpret results using Cox proportional hazards model
  • use extended Cox model to incorporate time-dependent covariates and competing risks
  • understand how the results of different survival analysis models can contribute to decision-modelling framework
  • perform survival analysis using R and interpret outputs from the survival R package. 

Course fees

Three day in-person survival course 10 - 12 December

£225 Oxford student

£400 Oxford staff

 

Optional Introduction to R one-day course 9 December

£75 Oxford Student

£150 Oxford staff

 

To register, please complete this application form. Once your application form is approved, we will send you a link for payment.

If you have any queries about this course, please contact: epi.courses@ndph.ox.ac.uk