The purpose of Multilevel models, also known as mixed models are used to analyse correlated observations. Correlated observations can occur, for instance, when subjects are clustered within neighbourhoods, patients are clustered within hospitals, students are clustered within schools, etc. Besides this, correlated observations also occur in longitudinal studies where the repeated measurements over time are clustered within each individual. Multilevel analysis provides a very elegant and powerful tool to deal with this clustering, i.e. to deal with correlated observations. For longitudinal data analysis, besides multilevel analysis, also other methods, such as GLM for repeated measures and generalised estimating equation (GEE) analysis, are available.
This six-day course will explain the basic concepts of multilevel analysis, some specific application of multilevel analysis and will further focus on longitudinal data analysis. The latter includes standard modelling, alternative modelling and the analysis of RCT data. It is an applied course, so the emphasis lies on the interpretation of the results from the different analyses and not on the mathematical background. Lectures are given in the morning and in the afternoon a computer practical is given using the statistical programs STATA, SPSS and R.
If a course is [Full], you can still register, but you will be placed on a waiting list. We will contact you as soon as a place becomes available. You can then decide whether you still want to join the course.
Multilevel models, also known as mixed models are used to analyse correlated observations. Correlated observations can occur, for instance, when subjects are clustered within neighbourhoods, patients are clustered within hospitals, students are clustered within schools, etc. Besides this, correlated observations also occur in longitudinal studies where the repeated measurements over time are clustered within each individual. Multilevel analysis provides a very elegant and powerful tool to deal with this clustering, i.e. to deal with correlated observations. For longitudinal data analysis, besides multilevel analysis, also other methods, such as GLM for repeated measures and generalised estimating equation (GEE) analysis, are available.
The course is designed for researchers who work with mixed model analysis, or researchers who plan to work with mixed model analysis. It is an applied course, so the mathematics behind the mixed model analysis is not discussed in detail.
In order to meet the entry requirements for this course, students must complete the EpidM course Regressietechnieken (V30), or demonstrate comparable prior knowledge. If you have not taken our course Regressietechnieken (V30), please mention your prior knowledge on the application form (in the comments box) and briefly describe how you obtained it. The course coordinator will decide whether you can be admitted to the course.
The course materials (lectures, assignments, feedback of the assignments etc) are available on Canvas, our digital learning environment. The documents will remain available on Canvas for at least one year.
In order to do the computer practicals, you will need:
1. STATA; if you don’t have STATA installed yet, you may be able to get it through your employer. Employees of Amsterdam UMC can request access to STATA at the ICT department. Employees of Radboud University Nijmegen can purchase STATA on Surfspot.
Unfortunately, STATA does not have trial versions.
and
2. SPSS; If you do not have SPSS installed yet, you can purchase it through Surfspot at a very reasonable price. Another option is to use IBM’s trial version: SPSS Software | IBM
Please note:
1. If you can’t get access STATA, it is also possible to do all practicals with SPSS.2. STATA and/or SPSS is the standard software to be used for the computer practical. However, if you are an experienced R user, you can also do the assignments in R independently. Answer keys are available, but the practical is not supported in terms of guidance in R.
Twisk JWR. Applied mixed model analysis. A practical guide. Cambridge University Press, 2019ISBN: 978-1108480574 (hardback)ISBN: 978-1108727761 (Paperback).
Twisk JWR. Applied Longitudinal Data Analysis for Medical Science: A Practical Guide 3rd Edition. Cambridge University Press; 2023• Paperback : ISBN 978-1009288033• Hardcove : ISBN 978-100928804
These books provide a good overview of the material covered. These books are compulsory reading for students who follow the entire Master’s program in Epidemiology.
Students participating in the course as part of the Master’s programme Epidemiology need to pass the exam in order to complete the course.
Students not participating in Master’s programme Epidemiology who sign up for this course as a separate / single course can optionally register for the exam. The examination fee is € 160 per registration.
You can register for the exam via the website: Exams. Registration will close 3 weeks prior to the exam.
Please note that you need to pass the exam in order to receive credits (EC).
A certificate of participation will be granted to all students who have attended at least 80% of the classes. The number of contact hours will stated on the certificate.
Only for Dutch medical specialists!If you wish to be considered for accreditation points by the KNMG (PE-points), you must sign the attendance list on the final day of the course.
To qualify for these points, there is an attendance requirement of 100%.
Programme Director EpidM, Professor in Applied biostatistics in longitudinal research, Amsterdam UMC
