Multilevel modelling of medical data
- 7 October 2002
- journal article
- review article
- Published by Wiley in Statistics in Medicine
- Vol. 21 (21), 3291-3315
- https://doi.org/10.1002/sim.1264
Abstract
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.Keywords
This publication has 41 references indexed in Scilit:
- A Two-Part Random-Effects Model for Semicontinuous Longitudinal DataJournal of the American Statistical Association, 2001
- Marginalized multilevel models and likelihood inference (with comments and a rejoinder by the authors)Statistical Science, 2000
- Comparisons of Software Packages for Generalized Linear Multilevel ModelsThe American Statistician, 1999
- Multilevel Modeling of Educational Data With Cross-Classification and Missing Identification for UnitsJournal of Educational and Behavioral Statistics, 1998
- Multilevel time series models with applications to repeated measures dataStatistics in Medicine, 1994
- Efficient Analysis of Mixed Hierarchical and Cross-Classified Random Structures Using a Multilevel ModelJournal of Educational and Behavioral Statistics, 1994
- A Crossed Random Effects Model for Unbalanced Data With Applications in Cross-Sectional and Longitudinal ResearchJournal of Educational Statistics, 1993
- A Crossed Random Effects Model for Unbalanced Data with Applications in Cross-Sectional and Longitudinal ResearchJournal of Educational Statistics, 1993