• Startdatum:
  • 31 mei 2021
  • Cursusduur:
  • 5 dagen
  • Werkzaam als:
  • PhD

Repeated measurements in clinical and epidemiological research

The course covers statistical methods to be used in the situation where one or more outcome variables are repeatedly measured in time on the same experimental unit. For instance, in a clinical trial, the outcome variable can be measured at baseline and at different times during the treatment period. For this type of data, traditional regression models cannot be used since outcomes of the same subject may be correlated, and this should be taken into account in the statistical model. Other examples of studies where there is a similar dependency in the outcome measurements are cluster randomised trials and meta-analysis. In the last one or two decades, much progress has been made in the development of new methods of analysis for dependent outcome data. In recent years several of these new methods have been implemented in commercially available computer packages. In the course, first an overview of classical approaches to repeated measurements will be given. Then modern methods are introduced. For approximately normally distributed response, focus will be on the General Linear Mixed Model. For non-normal response, the generalized estimating equations (GEE) approach for marginal models is discussed. Also some attention will be paid to random effects model, for instance random effects logistic regression. Examples of clinical and epidemiological applications will be given. In the computer labs, exercises with R and SPSS are used to get experience with applying these new methods to real data.

Prerequisites: Familiarity with standard regression models such as the multiple linear regression and logistic regression model. No pre-knowledge of repeated measurements analysis is required. Familiarity with data processing in R and/or SPSS. The participants may use either R or SPSS during the practicals. Solutions for both software will be provided.

The material will be covered using lectures and practical sessions. At its greatest majority the course will be given in a blended learning style integrating online media as well as traditional face-to-face teaching using zoom online meetings.
- During the lectures the theory will be covered and worked-out examples will be discussed. The lectures will be given mainly with online media combined with face-to-face teaching sessions where a short review of the material will be provided followed by questions and discussions on the covered topics.
- During the practical sessions, the theory covered will be applied by analysing real datasets

  CONCEPT PROGRAM
  Monday 31 May 2021
08:45 Online welcome 
09:00 Lectures
13:30 Practical exercises
16:30 Plenary discussion

 

  Tuesday 1 June 2021
08:55 Online welcome
09:00 Lectures
13:30 Practical exercises
16:30 Plenary discussion

 

  Wednesday 2 June 2021
08:55 Online welcome
09:00 Lectures
13:30 Practical exercises
16:30 Plenary discussion

 

  Thursday 3 June 2021
08:55 Online welcome
09:00 Lectures
13:30 Practical exercises
16:30 Plenary discussion

 

  Friday 4 June 2021
08:55 Online welcome
09:00 Lectures
13:30 Practical exercises
16:30 Plenary discussion
Dr. S. Tsonaka
Online
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Participation is free of charge* for students of the Leiden University or VU University. 

  • Please fill in your student email address and your student number.
  • Please note that a fee will be charged to those who do not attend courses or who are too late cancelling their participation of the course.
Course fee € 450,-
Fee for employees/PhD students LUMC / Prinses Maxima Hosptal € 150,-
Fee for students of the Leiden University or VU University Free of Charge
Fee for students outside Leiden University € 75,-