Survival Analysis

Course goals

ALL PARTICIPANTS WILL BE PLACED ON THE WAITING LIST UNTIL TWO WEEKS BEFORE THE START OF THE COURSE

GRADUATE STUDENTS:
Please be aware that you can only select a course option that shows the academic year and is offered Face-to-Face (F2F)

POSTGRADUATE STUDENTS:
Please be aware that you can only select a course option that shows the academic year and is offered Face-to-Face (F2F)  or online (depending on your registration)

(FYI: the other options are options for Continuing Education (onderwijs voor professionals))


At the end of the course, the student should be able to:

• recognize or describe the type of problem addressed by a survival analysis
• define and recognize censored data
• define and interpret a survivor function and a hazard function, and describe their relation
• recognize the computer printout from a Cox proportional hazards model, a stratified Cox model, and a Cox model extended for time-dependent covariates
• state the meaning of the proportional hazards assumption and know how to check this assumption
• recognize which survival analysis technique is appropriate for a given research question and dataset
• interpret the computer printout for survival models, including hazard ratios, hypothesis testing, and confidence intervals

Content

Contact details: Educational Office Epidemiology
E-mail: msc-epidemiology@umcutrecht.nl

Registration:
Face-to-Face: You can register for this course via Osiris Student. More information about the registration procedure can be found here on the Students' site. NOTE Students of the MSc Epidemiology (Post Graduate) that register in time (i.e. at least two weeks before the start of a course) will always be admitted to the course unless it is completely full. Other students will receive information about their application two weeks before the start of the course.
Online: Online courses are only available for Epidemiology Postgraduate students and can register via Osiris Student. More information about the registration procedure can be found here on the Students' site.

Course coordinator:
Dr. R.K. (Rebecca) Stellato, UMC Utrecht, Julius Center for Health Sciences and Primary Care, Utrecht, the Netherlands

Course description:
Survival data, or more generally, time-to-event data (where the “event” can be death,  disease, recovery, relapse or another outcome), is frequently encountered in epidemiologic studies. Censoring is a problem characteristic to most survival data, and requires special data analytic techniques.

This course will give an introduction to survival analysis and cover many of the types of survival data and analysis techniques regularly encountered in epidemiologic research. The necessary statistical theory will be presented, but the course will focus on practical examples, with an emphasis on matching data analysis to the research question at hand. Lab sessions will give students the opportunity to apply the theory to real datasets.

Note: both SPSS and R will be used during lectures and computer labs. While most techniques covered can be performed in SPSS, several require the use of R (or another package, such as Stata or SAS). Those unfamiliar with the (free) statistical package R are strongly encouraged to practice with it before beginning the course.

Literature/study material used:
-
  
Mandatory for students in own Master’s programme:
MIght be for a specialization programme of Epidemiology & Epidemiology Postgraduate
 
Optional for students in other GSLS Master’s programme:
Yes
 
Prerequisite knowledge:
Classical Methods in Data Analysis
Modern Methods in Data Analysis (preferred)