Synopses & Reviews
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.
Synopsis
This new edition of this classic incorporates the most recent thinking on methodology and software, as well as the latest literature on multilevel statistical models. Topics covered by multilevel models have increased in recent years, and the methods are widely applied in the social sciences as well as in areas such as epidemiology, geography, education, surveys, and medicine. This third edition includes chapters on meta analysis, factor analysis and structural equation models, and has expanded sections on MCMC methods.
Synopsis
Includes bibliographical references (p. [231]-239) and indexes.
Synopsis
In the mid 1980s a number of researchers began to pursue systematic approaches to the statistical modelling and analysis of hierarchically structured data. Aitkin's early work on teaching styles and his subsequent classic work with Longford initiated a series of developments that by the early 1990s had resulted in a core of established techniques and software. The methods are now finding wide applications in education, epidemiology, geography, child development, and sociology. This new edition aims to integrate existing methodological developments, provide examples, and explain new developments, especially in discrete response data, times series models, random cross classifications, errors of measurement, missing data, and nonlinear models.
About the Author
Harvey Goldstein, FBA is Director of the International Centre for Research on Assessment, Institute of Education, London, UK.
Table of Contents
Preface
Acknowledgements
Notation
Glossary
1. Introduction
2. The Basic Linear Multilevel Model and its Estimation
3. Extensions to the Basic Multilevel Model
4. The Multivariate Multilevel Model
5. Nonlinear Multilevel Models
6. Models for Repeated Measures Data
7. Multilevel Models for Discrete Response Data
8. Multilevel Cross Classification
9. Multilevel Event History Models
10. Multilevel Models with Measurement Errors
11. Software for Multilevel Modelling; Missing Data and Multilevel Structural Equation Models
References
Author Index
Subject Index