Multilevel Statistical Models

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Throughout the social, medical and other sciences the importance of understanding complex hierarchical data structures is well understood

A thorough understanding of these techniques is therefore important for all those working in these areas

Applied statisticians in the social sciences, economics, biological and medical disciplines will find this book beneficial.

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

Illustrated throughout with real-life examples, explaining theoretical concepts

Key Features Provides a clear introduction and a comprehensive account of multilevel models

Multilevel modelling is now the accepted statistical technique for handling such data and is widely available in computer software packages

New methodological developments and applications are explored

This book is suitable as a comprehensive text for postgraduate courses, as well as a general reference guide

This new edition of Multilevel Statistical Models brings these techniques together, starting from basic ideas and illustrating how more complex models are derived

Written by a leading expert in the field of multilevel methodology

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