Survival Analysis

This course will be given in the academic year 2026–2027.

Many research questions in health sciences involve the time between a starting event and an outcome of interest. For example, researchers may study the time between a first heart attack and a subsequent heart attack, the length of a hospital stay, the time between prolonged exposure to a carcinogen and the development of cancer, or the time required for recovery after treatment. These durations are often referred to as survival times.

In this course, you will learn how to analyse and interpret survival data and answer important research questions such as: Do survival times differ between treatment and control groups? Which patient characteristics are associated with a better or worse prognosis? How can multiple prognostic factors be combined to predict outcomes?

A unique challenge in survival analysis is that, by the end of a study, the event of interest may not have occurred for all participants. As a result, the exact survival time is unknown for some individuals. These observations, known as censored data, require specialized statistical methods. This course introduces the most widely used techniques for analysing survival data and provides hands-on experience with real-world health research applications.

Gavin van der Nest
Department of Methodology & Statistics (DEB1)
+31 43 388 22 80

PhD candidates from the Faculty of Health, Medicine and Life Sciences

A prerequisite for participating in this course is that you have successfully completed the courses Introduction to Statistics Part 1 and Regression Analysis, Statistics Part 2.

• Kaplan-Meier survival curves
• Log-rank test
• Hazard ratio and confidence interval for hazard ratio
• Cox regression with multiple prognosis factors
• Cox regression with time-dependent covariates

4 sessions, of 2 hours each.

Literature, provided by the tutor

PhD candidates (Promovendi) of FHML, M4I and MERLN: no fee

These courses are free of charge in case you are employed or registered as FHML PhD candidate. 
Others: €400,00 (Prices are subject to change)
PhD candidates are given preference. 

PhD Office FHML
Available Monday, Tuesday, Thursday and Friday: 9 am – 5 pm

Phone: +31 43 38 84122
Visiting address: P. Debeyelaan 15, L. van Kleeftoren, 5.N2.030
aioonderwijs@maastrichtuniversity.nl