• Startdatum:
  • 20 juni 2022
  • Cursusduur:
  • 10 dagen
  • Werkzaam als:
  • PhD

BELOW INFORMATION IS SUBJECT TO CHANGE; PENDING LUMC POLICY AND COVID MEASUREMENTS. REGISTRATION WILL BE LAUNCHED BY MID DECEMBER.

Introduction
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.

Course material
All study materials are supplied electronically only. The material will be covered in lectures and practical sessions. The course will be given in a blended learning style integrating online media as well as traditional face-to-face teaching on campus.

  • 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

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.

Teaching environment
Spread over 10 days; every other day plenary introductions by the teacher in the morning, followed by self-study video's and practical assignments, and plenary discussions at the end of the course days about the course material of that day.

Certificate of Attendance / Assignment 
A post-course exam will have to be completed in the week after the course for those who need the ECTS  (1.5).The link to the exam will be distributed on Friday 1 July. The deadline for submitting the exam results is on Friday 18 July. In general; to obtain a certificate of participation, all lectures and practical exercise sessions should be attended. 

Language
Course material and lectures are in English.

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

Organizing committee

  • Dr. S. Tsonaka
  PRELIMINARY PROGRAM
  MONDAY 20 JUNE 2022
08:45 Registration
09:00 Opening session
Dr. Roula Tsonaka, LUMC
Location: Collegezaal 3
10:00 Plenary discussion 
Dr. Roula Tsonaka, LUMC 
Location: Collegezaal 3
13:00 Self study - lectures (videos) & practical exercises
Room V2-26 is available as of from 12:30hrs for students to work on campus
17:00 End of course day

 

  WEDNESDAY 22 JUNE 2022
09:45 Registration
10:00 Plenary discussion
Dr. Roula Tsonaka, LUMC
Location: Collegezaal 3
12:30 Self study - lectures (videos) & practical exercises
Room V2-26 is available for students to work on campus
17:00 End of course day

 

  FRIDAY 24 JUNE 2022
09:45 Registration
10:00 Plenary discussion
Dr. Roula Tsonaka, LUMC
Location: Collegezaal 3
12:30 Self study - lectures (videos) & practical exercises
Room V2-26 is available for students to work on campus
17:00 End of course day           
   
  TUESDAY 28 JUNE 2022
09:45 Registration
10:00 Plenary discussion
Dr. Roula Tsonaka, LUMC
Location: Collegezaal 3
12:30 Self study - lectures (videos) & practical exercises
Room V2-26 is available for students to work on campus
17:00 End of course day

 

  THURSDAY 30 JUNE 2022
09:45 Registration
10:00 Plenary discussion
Dr. Roula Tsonaka, LUMC
Location: Collegezaal 3
12:30 Self study - lectures (videos) & practical exercises
Room V2-26 is available for students to work on campus
17:00 End of course
   
  POST-COURSE ASSIGNMENT (via learning environment)
  Monday 4 July - Friday 8 July 2022
   
  POST-COURSE ASSIGNMENT (RESIT) (via learning environment)
  Monday 18 July - Friday 22 July 2022
   
  POST-COURSE - REVIEW RESULT ASSIGNMENTS (via learning environment)
Monday 25 July - Sunday 31 July 2022
Dr. S. Tsonaka
LUMC
,

LUMC
Gebouw: 1 & 3
Collegezaal 3 (gebouw 1)  & V2-26 (gebouw 3)

Parkeren en bereikbaarheid LUMC

To be determined. Prices will be announced in due course.