Multilevel modelling of medical data.
This tutorial presents an overview of multilevel or hierarchical data modelling and its applications in medicine. A description of the basic model for nested data is given and it is shown how this can be extended to fit flexible models for repeated measures data and more complex structures involving cross-classifications and multiple membership patterns within the software package MLwiN. A variety of response types are covered and both frequentist and Bayesian estimation methods are described.
Goldstein
Harvey
H
Institute of Education, University of London, London, UK. h.goldstein@ioe.ac.uk
Browne
William
W
Rasbash
Jon
J
D000465:Algorithms; D001499:Bayes Theorem; D006801:Humans; D016013:Likelihood Functions; D015201:Meta-Analysis as Topic; D015233:Models, Statistical; D015999:Multivariate Analysis; D016016:Proportional Hazards Models; D012984:Software; D016019:Survival Analysis