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...

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Veröffentlicht in:	Statistics in medicine 2002-11, Vol.21 (21), p.3291-3315
Hauptverfasser:	Goldstein, Harvey, Browne, William, Rasbash, Jon
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Bayes Theorem Biological and medical sciences complex data structures Humans Likelihood Functions Medical sciences Meta-Analysis as Topic mixed model mixed model, multilevel model Models, Statistical multilevel model Multivariate Analysis Proportional Hazards Models random effects model repeated measures Software Survival Analysis
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Beschreibung
Zusammenfassung:	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.
ISSN:	0277-6715 1097-0258
DOI:	10.1002/sim.1264