In follow-up studies, interest may be in the duration between a specific starting event, such as an initial heart attack, and a specific end event, such as a subsequent heart attack. Other examples of durations, called survival times, are the time between hospital admission and discharge, the time between start of a prolonged exposure to carcinogens and occurrence of cancer, and the recovery time. The following questions may be of importance: are survival times different between treatment and control groups? What is the prognostic value of a certain factor, or combination of factors? Once the follow-up has been completed, the end event may be unavailable for certain individuals if their end event has not yet occurred. These incomplete durations, called censured data, must be accurately recorded in the statistical analysis.
- 4 sessions, of 2 hours each
- 2 ECTS
- minimum 7, maximum 25 candidates
- intended for PhD candidates of FHML, MaCSBIO, M4I and MERLN
Department of Methodology & Statistics (DEB1)
+31 43 388 22 80
PhD candidates from the Faculty of Health, Medicine and Life Sciences
Required prior knowledge
A prerequisite for participating in this course is that you have succesfully 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, MaCSBIO, M41 and MERLN: not applicable.
0830-Survival Analysis – Sophie Vanbelle (MAX 25 personen)
|UNS50 - K4.485|
|Thursday||11-11-2021||8.30-10.30hrs.||UNS50 - K4.485|
|Thursday||18-11-2021||8.30-10.30hrs.||UNS50 - K4.485|
|Thursday||25-11-2021||8.30-10.30hrs.||UNS50 - K4.485|
Note: we are not yet sure how education will be given in the coming academic year and that the students have to take into account that the dates may change.Phone: Information
+31 43 387 28 44
Tuesday - Thursday 09.00 - 17.00
Min/Max PhD candidates:
minimum 7, maximum 25