Multilevel Analysis: An Introduction To Basic And Advanced Multilevel Modeling

This is the best, most basic text on linear mixed models. It begins with the ANOVA approach and so provides an excellent understanding of the underlying conceptual framework. Raudenbush & Bryk is also excellent but is presented at a higher level.

Snijders and Bosker's Multilevel Analysis is mathematically demanding but more readable than Raudenbush and Bryk's Hierarchical Linear Models. Snijders and Bosker's text would be much more useful for the less-experienced reader if it contained a directory identifying essential material. As is often the case with books of this kind, it is difficult to distinguish between really important topics, those crucial to understanding multilevel models, and ancillary topics which can be treated as non-essential, at least for the first pass through this dense and difficult material.It would also help if the authors located multilevel modeling within a statistical context likely to contain material that readers already understand. As it is, multilevel analysis is treated as a separate and new topic, and is readily accessible only to those with generalized mathematical maturity.The authors do, however, cover a broad range of pertinent material. Thus, while it is not a good choice for beginners looking for a self-instructional tool, the statistically sophisticated reader will find it to be an excellent reference. While just as difficult to understand as the rest of the book, Snijders and Bosker's develop some really informative and interesting examples of three-level models.This text has been in print for a decade, and is still widely used. I've found that as I become more familiar with multilevel modeling, the book becomes more valuable.

Very helpful. I have been able to use this book to walk myself through the analysis and I really understand what I'm doing. But, the authors say you don't need to know anything about statistics really to use this book. That is false. I do have a strong statistical background in my education, but I do not think it is easy for a beginner to understand.

I was required to use this book, but I chose to pair it with the Raudenbush & Bryk text while taking an applied HLM course. The book was thorough, although often unhelpful for someone who is in the process of designing their own study and preparing to conduct analyses. This book offered little help on data preparation, identifying problems with your data, and using software to conduct analyses. Not a bad book, but definitely needs to be used with a course where you have an instructor available to you.

This resource by Snijders provides a great reference for multilevel analyses. The descriptions and information are clearly presented. The variety of samples pooled from, for this reference book, came from a number of different fields - you won't get tired of reading about students in classrooms as with most other multilevel or HLM books. The information is slightly different than what I have found in other multilevel books, giving the reader a different perspective on some key concepts relating to multilevel analysis.

Makes understanding a somewhat difficult topic easier.

It's a very well-written book, even for sophisticated statisticians who may want to learn how to use the multilevel techniques in real practices. I recommend this book to everyone who would use the multilevel in their work, research, etc.

Useful, but maybe not the most user friendly

Good book

Nice book, it is quite clear, but in some chapters the explanations and example may get a bit too complex.

An accessible introduction to multilevel modelling; I recommend it.

I used this book as a textbook for a graduate course in application of mixed models with a mix of students from fields like mathematical statistics and quantitative psychology. It was accessible and stimulating for all students, providing a solid understanding of both basic and more subtle advanced concepts in mixed models.

Klare und einfach Einführung in die Welt der Multi-Level-Analysen.Allerdings währe es gut wenn auch Syntaxen für die gängigsten Statistikprogramme (SPSS, STATA, R, M Plus) erörtert worden wären.Dafür empfehle ich Tabachnik & Fidell. Allerdings geht Tom Snjiders deutlich mehr in die Tiefe.