Introducing Multilevel Modeling (Introducing Statistical Methods series) Review

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(More customer reviews)When analysing data, the relationships between people that belong in the same classroom, live in the same street or suburb, are part of the same family or therapy group,etc., are often ignored. Multilevel or hierarchical linear modelling is a statistical technique for taking into account such dependencies, arranged in hierarchies (e.g., correlations between students within classrooms, correlations between classrooms within schools, correlations between schools within school districts). In other words, multilevel modeling techniques attempt to model the hierarchical relationships that are found in the real world. In the last 10 years or so there has been a growing number of books and software packages concerned with multilevel analyses. Introducing Multilevel Modeling is shorter and slightly less 'mathematical' than most and gives quite a good introduction to the subject. The book makes reference to the British MLn (MLWiN) computer program in its examples, whereas an introductory text arguably should have used the HLM program, for which a cutdown student version is available free. Taking group dependencies into account is extremely important, but unfortunately many researchers will be discouraged by the dry and heavy-going feel of these texts, which is so often the case with anything involving statistical theory. A highly approachable and readable book remains to be written, but Introducing Multilevel Modeling is probably the best of the current crop.

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This is the first accessible and practical guide to using multilevel models in social research.



Multilevel approaches are becoming increasingly important in social, behavioural, and educational research and it is clear from recent developments that such models are seen as being more realistic, and potentially more revealing, than ordinary regression models.



While other books describe these multilevel models in considerable detail none focuses on the practical issues and potential problems of doing multilevel analyses that are covered in Introducing Multilevel Modeling.



The authors' approach is user-oriented and the formal mathematics and statistics are kept to a minimum. Other key fe

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