WR05: Mixed models

This four-day course will explain the basic concepts of mixed models. It is an applied course, so the emphasis lies on the interpretation of the results from the mixed model analyses and not on the mathematical background. The course centres on the two most important applications of mixed models – multilevel analysis and longitudinal data analysis. Lectures are given in the morning and in the afternoon a computer practical is given using the statistical programs STATA, SPSS and MLwiN.

Date:
18, 19, 22, 23 January 2018 Tuition fee: € 1.275,-
City:
Amsterdam
Course coordinator:
Prof. dr. J.W.R. Twisk
Language:
English
Learning method:
Lectures and computerpractical
Examination:
Written exam (facultative)
Examination dates:
See schedule at 'Tentamens'
Number of EC:
3
  • Course discription and topics

    Mixed models are used to analyse correlated observations. Correlated observationsobservations 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 for each individual. Mixed model analysis provides a very elegant and powerful tool to deal with this clustering, i.e. to deal with correlated observations.

    This four-day course will explain the basic concepts of mixed models. It is an applied course, so the emphasis lies on the interpretation of the results from the mixed model analyses and not on the mathematical background. The course centres on the two most important applications of mixed models – multilevel analysis and longitudinal data analysis. Lectures are given in the morning and in the afternoon a computer practical is given using the statistical programs STATA, SPSS and MLwiN.

    The following topics are discussed during the course:
    • Basic principles of mixed model analyses
    • Example of a mixed model analysis with a two-level structure
    • Example of a mixed model with a three-level structure
    • Logistic mixed model analysis
    • The use of mixed model analyses in longitudinal studies
    • Other methods of analysing longitudinal data
    • Comparison between the different methods of analysing longitudinal data
    • Alternative models for analysing longitudinal data
    • Sample size calculations
    • Software for mixed model analysis

    Programme

    Day 1
    • Background of mixed model analysis
    • Mixed model analysis with a two-level structure
    • Mixed model analysis with a three-level structure
    • Computer practical

    Day 2
    • Logistic mixed model analysis
    • The use of mixed model analysis in longitudinal studies
    • Computer practical

    Day 3
    • Other methods of analysing longitudinal data
    • Comparison between different methods of analysing longitudinal data
    • Computer practical

    Day 4
    • Alternative models for longitudinal data analysis
    • Sample size calculations
    • Software
    • Computer practical.

  • Faculty
    Prof. Jos W.R. Twisk, PhD, course coordinator
    Professor of Applied Biostatistics
    Department of Epidemiology & Biostatistics. VU University Medical Center, Amsterdam and Department of Health Sciences, VU University, Amsterdam

    Professor Jos Twisk is head of the expertise center for applied longitudinal data analysis and he wrote textbooks for applied longitudinal data analysis, multilevel analysis and an introduction to applied biostatistics. Furthermore, he (co)-authored more than 400 international peer reviewed papers.

    Iris Eekhout, PhD
    Department of Epidemiology & Biostatistics. VU University Medical Center, Amsterdam
    UMCU, militaire geestelijke gezondheidszorg (MGGZ) van het Ministerie van Defensie

    Iris Eekhout finished a master in Clinical Psychology and a master in Methodology and Statistics at the University of Leiden, She is aan expert in missing data methods applied in epidemiological and medical research. Especially, methods to handle missing questionnaire items and total scores.

  • Learning objectives

    • The student understands the basic principles of mixed model analysis
    • The student understands the role of mixed model analysis in analysing longitudinal data
    • The student understands the differences between different methods of analysing longitudinal data
    • The student understands how alternative models can be used to answer specific research questions
    • The student is capable of performing a mixed model analysis using various software programs.
    • The student understands the output of a mixed model analysis and is capable of interpreting this output.

  • Course pre-requisites and target group

    It is assumed that the students are familiar with the principles of linear and logistic regression analysis.

    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 material and literature

    On the first day of the course you will receive a course pack containing copies of all lecture presentations, assignments, and feedback on these assignments.

    Recommended reading

    Twisk JWR. Applied Longitudinal Data Analysis for Epidemiology. 2nd Revised edition, Cambridge University Press, 2013. ISBN 97 811 076 9992 2.

    Twisk JWR. Applied Multilevel Analysis. A Practical Guide. Cambridge University Press. 2006. ISBN 97 805 216 1498 6.

  • Exam and accreditation

    Exam

    Participants who take this course as part of the Master Epidemiology always complete the course with an exam. Other participants can choose if they want to complete the course with an exam.
    The exam will be in English. Only when you pass the exam you get a certificate showing the credits (study points/EC).
    The examination dates can be found on the website of EpidM.

    Anyone who wants to participate in the examination should apply at least four weeks before the exam to register via the website: https://epidm.nl/nl/tentamens/

    The examination material of reference and questions to practice can be found on the intranet page of the course (see above).

    During the examinations of EpidM the use of e-books is forbidden

    Accreditation points

    Only for Dutch students!
    If you wish to be considered for accreditation points connected to this course, you must sign the attendance list on the last day of the course.

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

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