Throughout the social, medical and other sciences the importance of
understanding complex hierarchical data structures is well
understood. Multilevel modelling is now the accepted statistical
technique for handling such data and is widely available in
computer software packages. A thorough understanding of these
techniques is therefore important for all those working in these
areas. This new edition of Multilevel Statistical Models brings
these techniques together, starting from basic ideas and
illustrating how more complex models are derived. Bayesian
methodology using MCMC has been extended along with new material on
smoothing models, multivariate responses, missing data, latent
normal transformations for discrete responses, structural equation
modeling and survival models.
Key Features:
* Provides a clear introduction and a comprehensive account of
multilevel models.
* New methodological developments and applications are
explored.
* Written by a leading expert in the field of multilevel
methodology.
* Illustrated throughout with real-life examples, explaining
theoretical concepts.
This book is suitable as a comprehensive text for postgraduate
courses, as well as a general reference guide. Applied
statisticians in the social sciences, economics, biological and
medical disciplines will find this book beneficial.
About the author
Harvey Goldstein, Professor of social sciences, University of Bristol and Associate Editor for the Statistical Modelling Journal, and previous Editor of the Royal Statistical Society’s Journal, Series A.
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