• Start date:
  • 17 May 2021
  • Duration:
  • 5 days
  • Working as:
  • PhD

Introduction
Survival analysis is the study of the distribution of life times, i.e. the times from an initiating event (birth, diagnosis, start of treatment) to some terminal event (relapse, death). This type of data analysis is most prominently (but not only) used in the biomedical sciences. A special feature of survival data is that it takes time to observe the event of interest. As a result for a number of subjects the event is not observed, but instead it is known that it has not taken place yet. This phenomenon is called censoring and it requires special statistical methods.

During the course different types of censored data will be introduced and techniques for estimating the survival function by employing non-parametric methods will be illustrated. Multiplicative hazards regression models , testing and inference techniques will be studied in great details. Special aspects as time-dependent covariates effects, stratification, time and prediction will be introduced. Techniques to be used to assess the validity of the hazard regression model will be discussed. Alternative to Cox model will be illustrated and predictive models will be introduced. The last part of the course focus on more advanced models like competing risks and multi-states.

A competing risks model is concerned with failure time data where each subject may experience one of the K different type of terminal events. Multi-states are employed when some intermediate events may occur before the final event of interest and one is interested in the effects of the occurrence of those intermediate events on the final events. Also for these more complex models estimation and prediction techniques will be discussed. The course ends with a discussion about sample size calculations.

Practicals
Participants are requested to use their own laptop for following this course. SPSS, R or Stata software is required, for the practical assignments.  

Requirements
Basic knowledge of statistics (e.g. the Boerhaave course 'Basic methods and reasoning in Biostatistics') and of regression models (e.g. the Boerhaave course 'Regression Analysis')

Teaching environment
Morning lectures, self-study practical exercises, and daily plenary discussions with the teacher.

Proof of participation / exam / ECTS
In order to obtain a proof of participation, the complete course should be attended. A practical assignment/exam must be submitted at the end of the course for those who need ECTS. 
This course is  1,5 ECTS.

Course material
All study materials are supplied electronically only, and will be made available about 1 week prior to the course. 

Target group
Master and PhD students in the bio-medical sciences

Organizing committee

  • Prof. dr. Marta Fiocco, Mathematical Institute Leiden University and Biomedical Data Science Medical Statistical Section (m.fiocco@lumc.nl)

MONDAY 17 MAY 2021

08:45 Log-in / Registration
09:00 Introduction to survival analysis, lecture (mandatory)
10:00 Self-study assignment / video's 
12:30 Question moment with teacher (optional)
13:30 Self-study assignment / video's 
16:00 Plenary discussion of practical exercises (mandatory)
17:30 End of course - day 1

 

TUESDAY 18 MAY 2021

08:45 Log-in / Registration
09:00 Lecture (mandatory)
10:00 Self-study assignment / video's 
13:00 Question moment with teacher (optional)
13:30 Self-study assignment / video's 
16:00 Plenary discussion of practical exercises (mandatory)
17:30 End of course - day 2

 

WEDNESDAY 19 MAY 2021

08:45 Log-in / Registration
09:00 Morning Lecture (mandatory)
10:00 Self-study assignment / video's 
13:30 Question moment with teacher (optional)
14:00 Self-study assignment / video's 
16:00 Plenary discussion of practical exercises (mandatory)
17:30 End of course - day 3

THURSDAY 20 MAY 2021

08:45 Log-in / Registration
09:00 Morning lecture (mandatory)
10:00 Self-study assignement / video's 
13:00 Question moment with teacher (optional)
13:30 Self-study assignment / video's
16:00 Plenary discussion of practical exercises (mandatory)
17:30 End of course - day 4

 

FRIDAY 21 MAY 2021

08:45 Log-in / Registration
09:00 Morning Lecture (mandatory)
10:00 Self-study assignement / video's 
13:00 Question moment with teacher (optional)
13:30 Self-study assignment / video's
16:00 Plenary discussion of practical exercises (mandatory)
17:30 End of course - day 5
Prof. dr. M. Fiocco
G. Kantidakis
PhD student, LUMC
Online
,
Regular course fee € 450,-
Reduced fee for PhD students LUMC  € 150,-
Reduced fee for employees LUMC € 150,-
BA/MA students of the Leiden University  Free of charge *
Students of other universities (non Leiden University)             € 75,- *

* Limited places available. In order to validate your student registration, you must register with your student e-mail address and submit your student number on the registration form. In addition, a scan of your student pass will have to be submitted to boerhaavenacholing@lumc.nl. Please note that a € 45,- cancellation fee will be charged to students who do not attend the course (no show), or cancel their registration.