Back to Survival Analysis in R for Public Health
Imperial College London

Survival Analysis in R for Public Health

Welcome to Survival Analysis in R for Public Health! The three earlier courses in this series covered statistical thinking, correlation, linear regression and logistic regression. This one will show you how to run survival – or “time to event” – analysis, explaining what’s meant by familiar-sounding but deceptive terms like hazard and censoring, which have specific meanings in this context. Using the popular and completely free software R, you’ll learn how to take a data set from scratch, import it into R, run essential descriptive analyses to get to know the data’s features and quirks, and progress from Kaplan-Meier plots through to multiple Cox regression. You’ll use data simulated from real, messy patient-level data for patients admitted to hospital with heart failure and learn how to explore which factors predict their subsequent mortality. You’ll learn how to test model assumptions and fit to the data and some simple tricks to get round common problems that real public health data have. There will be mini-quizzes on the videos and the R exercises with feedback along the way to check your understanding. Prerequisites Some formulae are given to aid understanding, but this is not one of those courses where you need a mathematics degree to follow it. You will need basic numeracy (for example, we will not use calculus) and familiarity with graphical and tabular ways of presenting results. The three previous courses in the series explained concepts such as hypothesis testing, p values, confidence intervals, correlation and regression and showed how to install R and run basic commands. In this course, we will recap all these core ideas in brief, but if you are unfamiliar with them, then you may prefer to take the first course in particular, Statistical Thinking in Public Health, and perhaps also the second, on linear regression, before embarking on this one.

Status: Probability & Statistics
Status: Time Series Analysis and Forecasting
IntermediateCourse11 hours

Featured reviews

LY

5.0Reviewed Aug 23, 2020

What a great course it is!!! I could get the solid basic knowledge from the course.

YX

4.0Reviewed Nov 21, 2019

The final quiz is a little bit confusing ,pls provide detailed feedback on it so we can learn further even we did not pass it.

FA

5.0Reviewed Jul 21, 2019

Very nice introductory course on survival analysis in R. Exercises were well designed.

RR

5.0Reviewed Dec 30, 2020

The course is wonderful and very informative. Only feedback is the final quiz was pretty hard.

AB

5.0Reviewed Jun 14, 2020

Awesome course learned a lot from this entire series. Thank you!!!

VD

5.0Reviewed Aug 26, 2019

Good and practical introduction to survival analysis. I liked the emphasis on how to deal with practical data sets and data problems.

RP

5.0Reviewed Dec 28, 2020

Very well explained including aspects not commonly covered in other tutorials such as assumptions testing.

VA

4.0Reviewed Jan 29, 2021

Good intro, just wish there would be an intro to more advanced methods (e.g. time varying covariates).

JZ

5.0Reviewed Mar 14, 2020

Very good introduction course for survival analysis in R

AM

5.0Reviewed Oct 24, 2024

This was an excellent course, The explanations were so plain and good. Huge thanks to the instructor - Alex Bottle to making this course.

KM

5.0Reviewed May 29, 2020

Very enjoyable course, and simple but effective application using R which I know very well in my practice

AP

5.0Reviewed Jun 16, 2023

This a good course for those who want to dive into survival analysis.

All reviews

Showing: 20 of 73

Todd Daniel
4.0
Reviewed Nov 25, 2019
Amir Abdollahi
2.0
Reviewed May 16, 2019
Deleted Account
2.0
Reviewed Mar 5, 2019
Paco Cruz
1.0
Reviewed Jul 22, 2020
Kenil Cheng
1.0
Reviewed Feb 8, 2020
Retham Lai
3.0
Reviewed May 11, 2020
Sreya Pradhan
5.0
Reviewed Jan 4, 2020
Victoria Duthie
5.0
Reviewed Aug 26, 2019
Sandro Savino
5.0
Reviewed Sep 30, 2020
Merce Grau Perez
5.0
Reviewed May 25, 2020
Eleanor Hudson
5.0
Reviewed Jun 11, 2020
Nevin John
5.0
Reviewed Feb 1, 2020
Qusai Ahmed Khadder Abdulla Ali
5.0
Reviewed Nov 26, 2020
Lucas Gonzalez
5.0
Reviewed Nov 12, 2020
Yung-Tsai Chu (Chu, Yung-Tsai)
5.0
Reviewed Dec 30, 2021
Lesaffre Alain
5.0
Reviewed Jul 3, 2020
Johnason Xaviers
5.0
Reviewed May 10, 2020
Astghik Mikayelyan
5.0
Reviewed Oct 25, 2024
Assal hamza
5.0
Reviewed Aug 2, 2019
Roxana Popa
5.0
Reviewed Dec 29, 2020