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Multilevel modelling of medical data
Author(s) -
Goldstein Harvey,
Browne William,
Rasbash Jon
Publication year - 2002
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.1264
Subject(s) - frequentist inference , computer science , multilevel model , variety (cybernetics) , bayesian probability , hierarchical database model , data mining , r package , software , data type , data science , bayesian inference , machine learning , artificial intelligence , programming language
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. Copyright © 2002 John Wiley & Sons, Ltd.