Multilevel Analysis
An Introduction to Basic and Advanced Multilevel Modeling
- Tom A B Snijders - University of Groningen, Netherlands
- Roel J Bosker - University of Groningen, Netherlands
Quantitative/Statistical Research (General)
Snijders and Bosker's book is an applied, authoritative and accessible introduction to the topic, providing readers with a clear conceptual and practical understanding of all the main issues involved in designing multilevel studies and conducting multilevel analysis.
This book provides step-by-step coverage of:
• multilevel theories
• ecological fallacies
• the hierarchical linear model
• testing and model specification
• heteroscedasticity
• study designs
• longitudinal data
• multivariate multilevel models
• discrete dependent variables
There are also new chapters on:
• missing data
• multilevel modeling and survey weights
• Bayesian and MCMC estimation and latent-class models.
This book has been comprehensively revised and updated since the last edition, and now discusses modeling using HLM, MLwiN, SAS, Stata including GLLAMM, R, SPSS, Mplus, WinBugs, Latent Gold, and SuperMix.
This is a must-have text for any student, teacher or researcher with an interest in conducting or understanding multilevel analysis.
Tom A.B. Snijders is Professor of Statistics in the Social Sciences at the University of Oxford and Professor of Statistics and Methodology at the University of Groningen.
Roel J. Bosker is Professor of Education and Director of GION, Groningen Institute for Educational Research, at the University of Groningen.
This impressively clear textbook achieves its title's aim to be an introduction from basic to advanced multilevel modelling. Mathematical treatment is kept to the minimum to explain the differences between models, with an emphasis on intuitive understanding of concepts. This is very helpful to students who feel that moving up from regression/GLM to multilevel models is a big step.
I was especially impressed by the clear explanation of topics that are often described poorly by other authors, such as ICC and reliability, Hausman test (although the authors are unusual in never using the term 'endogeneity'), deviance tests and testing under ML/REML.
The 'Glommary' at the end of each chapter is a nice mix of glossary and a recap of major points. The examples are clear, varied and motivating.
The only problem I have with the book is the lack of examples with software. Although these are prone to becoming out of date, having a chapter on software gives little information to the newcomer unless they can see for themselves how the software is not forbiddingly esoteric. Many students feel anxious about using software even after they have grasped the theory.
This book provides a comprehensive coverage of multiple level theories and related models. Despite being an authoritative book in this field it should be used as a supplement for social science students because its content is not easily accessible.
A useful text for postgraduate students but I have to regard it only as a supplementary reading for my undergraduate students.
Most readable book on multilevel analysis. Very good presenting of the complex topic of multilevel models. I recommended the book for every student interested in advanced methods.
One of the best textbooks on multilevel analysis! Strongly recommended to my students.
An excellent textbook which covers a broad range of pertinent issues for Multilevel modelling. Indeed, an essential read for those wanting to better grasp this powerful method of statistical analysis.
This is a specialist book that provides clear guidance for doctoral researchers who are exploring complex nested relationships.
Well written textbook, however, due to its advanced statistical method, we only used it as supplemental reading for those students who were interested in some extra analysis. However, it makes a sophisticated method easier to understand and is a good alternative to Hox' classic "Multilevel Analysis".
An excellent applied text, providing the basics and moving onto much more detailed multilevel analysis.
