Course

Survival Analysis

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.

Instructor

Dr. A.W. Ambergen
Department of Methodology & Statistics (DEB1)
+31 43 388 22 80

Target group

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.

Content

  • 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

Meetings

4 sessions, of 2 hours each.

Method

Literature, provided by the tutor

Course fee

PhD candidates (Promovendi) of FHML, MaCSBIO, M41 and Merln: not applicable.
Others: €400,00.

Dates and times

 02-11-2017, 8.30-10.30 hrs, UNS40 K4.403 
 09-11-2017, 8.30-10.30 hrs, UNS40 K4.403
 16-11-2017, 8.30-10.30 hrs, UNS40 K4.403
 23-11-2017, 8.30-10.30 hrs, UNS40 K4.403

Information

PhD secretary
+31 43 388 56 13 
Mondays - Tuesdays and Thursdays 08.30 - 12.00
aioonderwijs[at]maastrichtuniversity[dot]nl

Code: 0830

Assessment: 
assignment

Min/Max PhD candidates: 
minimum 7, maximum 25

ECTS: