GESIS Training Courses
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Wiss. Koordination

Reinhard Schunck
Tel: +49 221 47694160

Administrative Koordination

Angelika Ruf
Tel: +49 221 47694-162

Week 1: Multilevel Analysis

Dozent(en):
Prof. Ian Brunton-Smith, PhD

Datum: 19.02 - 23.02.2018 ics-Datei

Seminarinhalt

This course introduces methods for modelling multilevel data structures, for example pupils nested within schools, or individuals nested within neighbourhoods. Starting with basic concepts in multilevel modelling and the fundamentals of random intercept and random coefficient models, the course will then cover more advanced topics including: nonlinear models for binary responses, repeated measures, multivariate models, cross-classified models, and spatial data structures.The course will use MLwiN.
 
 
Keywords
Multilevel, mixed effects, random effects, clustering


Zielgruppe

Participants will find the course useful if they
  • Are using data with a clustered data structure
  • Want to know more about the basic principles of multilevel models
  • Are interested in more advanced topics in multilevel modelling, including MCMC approaches for cross-classified and spatial data structures.


Lernziel

By the end of the course participants will
  • Be able to understand the ideas behind multilevel modelling and when their use is appropriate.
  • Be able to fit a range of random intercept and coefficient models to continuous and binary response data
  • Have a general understanding of MCMC methods and their application to multilevel modelling
  • Be able to deal with a range of complex data structures including hierarchical, cross-classified, repeated measures, multivariate, and spatial


Voraussetzungen

  • A basic understanding of statistical concepts
 


Zeitplan

Literaturempfehlungen

Referenteninformationen - Prof. Ian Brunton-Smith, PhD