Multilevel Analysis
An Introduction to Basic and Advanced Multilevel Modeling
- Tom A B Snijders - University of Groningen, Netherlands, University of Groningen, University of Oxford, UK; University of Groningen, The Netherlands
- Roel J Bosker - University of Groningen, Netherlands
The Second Edition of this classic text introduces the main methods, techniques, and issues involved in carrying out multilevel modeling and analysis.
Snijders and Boskers' 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
- Multi-stage sampling
- 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 for Surveys
- Bayesian and MCMC estimation and latent-class models.
This book has been comprehensively revised and updated since the last edition, and now includes guides to modeling using HLM, MLwiN, SAS, Stata including GLLAMM, R, SPSS, Mplus, WinBugs, Latent Gold, and Mix.
This is a must-have text for any student, teacher, or researcher with an interest in conducting or understanding multilevel analysis.
This is a nice introductory book for multilevel analysis. It is writing in a very easy way to understand the principle of the multilevel research. The book covers the main analysis that student could need in for example a final posgrade dissertation or even at a level of PhD dissertation.
I found the book useful for researchers who want to know more about multi level statistics.
A useful text for postgraduate students but I have to regard it only as a supplementary reading for my undergraduate students.
One of the best textbooks on multilevel analysis! Strongly recommended to my students.
This book provides a helpful and comprehensive introduction to the use of multi-level modelling.
The book is suitable for beginners due to the well understandable step by step explanations as well as advanced users due to deeper insight into specific topics and mathematical background. However more practical examples would benefit the learning. The book teaches more about the theoretical and statistical background and neglects the “how to” aspect. The online resources are rather scarce as well compared with other textbooks. Especially the lack of data files in different formats (e.g. for the HLM program) is a disadvantage.
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"."
too technical language; should cater more for the needs of the "average" scientist and practitioner; definitely not recommended for newcomers to the subject"
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.
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.
