Survival analysis in medical research

This course gives an introduction to the analysis of survival data that because of censoring requires special statistical
techniques. The students will be able to apply basic non-parametric methods and the Cox regression model using the statistical package Stata. They also learn how to investigate whether the imposed proportional hazards assumption is reasonable in a specific context.

Survival data often contains censored observation as for example when some patients are still alive at the end of the study. Analysis of such data requires special statistical techniques. The course introduces basic statistical concepts that are ty-pically targeted in survival analysis. Topics covered are: Non-parametric methods such as the Kaplan-Meier estimator and the log-rank test, parametric regression models, Cox-regression analysis including goodness-of-fit tools, survival prediction and competing risks.

Course credit: 3 ECTS.

Teaching arrangements
Lectures and exercises including use of computers. The typical arrangement is lectures for the first half of the day and individual coursework with exercises the second half.

Course leader: Postdoc Adam Lenart and postdoc Virginia Zarulli, Max-Planck Odense Center, Epidemiology, Biostatistics and Biodemography, SDU.

Prerequisites: Knowledge about Stata corresponding to what is acquired from the course “Datadokumentation og introduktion til brug af Stata” is preferable but not mandatory. Students should bring their own laptop.

Place: Winsløwparken..

Course Fee:
The course is free of charge for PhD students enrolled in Universities that have joined the "Open market agreement".
For other participants there is a course fee of DKK 4206,-

To give you the best possible experience, this site uses cookies  Read more about cookies

Accept cookies