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Multilevel Modelling and
Longitudinal Data Analysis (WK75)

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.

Course details

Date:
19, 20, 21, 24, 25, 26 January 2022
Tuition fee:
1.750
City: Amsterdam Course coordinator: Professor J.W.R. (Jos) Twisk, PhD
Language: English Learning method: Lectures and computerpractical
Examination: Written exam with computer assignment (facultative) Examination dates: See page Exams
Number of EC: 4 Details:
Date Tuition fee:
19, 20, 21, 24, 25, 26 January 2022
1.750
City: Amsterdam
Course coordinator: Professor J.W.R. (Jos) Twisk, PhD
Language: English
Learning method: Lectures and computerpractical
Examination: Written exam with computer assignment (facultative)
Examination dates: See page Exams
Number of EC: 4
Details:

About the course

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. At that time you can still decide whether you want to participate in the course.

More information

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.

  1. The student understands the basic principles of multilevel analysis and can make the right choices for an analytical strategy regarding multilevel data.
  2. The student is capable of interpreting the output of a multilevel analysis.
  3. The student understands the basic principles of of a longitudinal data analysis and is capable of interpreting the output of a longitudinal data analysis.
  4. The student is capable of analysing data from an RCT and interpreting the output of an RCT data analysis.
  5. The student is capable of performing a multilevel analysis and a longitudinal data analysis using various software programs
Target group

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.

Course pre-requisites

Participants need to have background knowledge of linear and logistic regression analysis on the level of the EpidM course Regression techniques 

Coursematerial

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.

To be able to do the computer practicals of this course you will need:

1.         STATA; if you do not have STATA on your laptop, you may be able to arrange STATA through your employer. STATA can be made available via VIEW for employees of the Amsterdam UMC location VUmc. Employees of the Amsterdam UMC location AMC can apply for STATA at AMC’s ICT. If you work at Radboud University Nijmegen, you can purchase STATA via Surfspot.

Unfortunately no trial versions are available for STATA.

and

2.         SPSS; if you don’t have SPSS on your laptop, you can purchase SPSS through Surfspot at a very reasonable price. If you do not want to purchase SPSS, you can use the trial version that IBM makes available. See SPSS Software | IBM

Please note:

1 if it is impossible to obtain STATA, it is also possible to do all practicals with SPSS.
2. if you only work with R, it is also possible to do the computer practicals with R.

Literature

Twisk JWR. Applied mixed model analysis. A practical guide. Cambridge University Press, 2019
ISBN: 978-1-108-48507-4 (hardback)
ISBN: 978-1-108-72776-1 (Paperback).

Twisk JWR. Applied Longitudinal Data Analysis for Epidemiology. 2nd Revised edition, Cambridge University Press, 2013. ISBN 9781107699922

 

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 € 150 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. Only contact hours are stated on this certificate.

Only for Dutch medical specialists!

If you wish to be considered for accreditation points by the KNMG , you must sign the attendance list on the last day of the course.

To qualify for the accreditation points, you must have been present the whole course.

Faculty