In recent years enormous advances in Bayesian methodology have resulted in a great expansion regarding the applications of Bayesian statistics in a wide range of fields. This up-to-date volume is designed to meet the growing need for a comprehensive treatment of modern Bayesian theory in readable form. Includes chapters on robustness and computation.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
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 new edition brings the book fully up to date, explaining important new developments such as the use of Markov Chain Monte Carlo methods, bootstrapping and mulitvariate 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.
Anthony O'Hagan, Professor of Statistics, University of Nottingham.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.