Reviews of previous edition:
'...enlivened with many examples...an elegant outline of
a class of statistical models...it is nicely produced and
clearly written.' International Statistical Institute
'This book is definitely to be recommended as a good clear
introduction to the subject, and as a starting point for detailed
research.' Mathematics Today
Key Features:
- The only comprehensive treatment of modern multilevel
modelling techniques
- The author is an internationally-renowned expert in the
field
- Provides a comprehensive reference to software tools
- A standard text for postgraduate courses as well as a
general reference.
Description:
It is now generally recognised in many areas of the social,
medical and other sciences that statistical data typically
have complex hierarchical or multilevel structures in which
individuals are grouped together in communities or institutions.
This grouping affects their behaviour and multilevel modelling
is now the accepted statistical technique for the analysis
of this type of data. An understanding of these methods is
vital for researchers in fields such as education, epidemiology,
geography, child growth and social surveys, among others.
This third edition of Multilevel Statistical Models brings
the book fully up-to-date, explaining important new developments
such as the use of Markov Chain Monte Carlo methods, bootstrapping
and multivariate models. The book has been completely restructured
for this third edition and extra space has been given to discussion
of key issues such as missing data, measurement errors and
multivariate models. Real-life examples are used throughout
to illustrate clearly the theoretical concepts.
Readership:
Applied statisticians in social, medical and educational
research. Postgraduates using these techniques as part of
their course.
Contents:
Preface
Acknowledgements
Notation
Glossary
1. An introduction to multilevel models
2. The basic 2-level model
3. Three level models and more complex hierarchical structures
4. Multilevel Models for discrete response data
5. Models for Repeated measures data
6. Multivariate multilevel data
7. Multilevel factor analysis and structural equation models
8. Nonlinear multilevel models
9. Multilevel modelling in sample surveys
10. Multilevel event history models
11. Cross classified data structures
12. Multiple membership models
13. Measurement errors in multilevel models
14. Missing data in multilevel models
15. Software for multilevel modelling, resources and further
developments
References
Author index
Subject index
Links:
Harvey Goldstein’s home page is at
http://www.ioe.ac.uk/hgpersonal/
Another useful site is the Centre for Multilevel Modelling
at
http://multilevel.ioe.ac.uk/
*
Please note, you are welcome to print the sample chapter files
for personal use but all material included in these files
is copyrighted to Hodder Arnold and is not for further distribution
without the permission of the publishers. In order to download
pdf files you will need Adobe Acrobat or Adobe Acrobat Reader
installed. Visit the Adobe
website to get this free software if necessary.
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