This is a practical introduction to multilevel analysis suitable for all those doing research. Most books on multilevel analysis are written by statisticians, and they focus on the mathematical background. These books are difficult for non-mathematical researchers. In contrast, this volume provides an accessible account on the application of multilevel analysis in research. It addresses the practical issues that confront those undertaking research and wanting to find the correct answers to research questions. This book is written for non-mathematical researchers and it explains when and how to use multilevel analysis. Many worked examples, with computer output, are given to illustrate and explain this subject. Datasets of the examples are available on the internet, so the reader can reanalyse the data. This approach will help to bridge the conceptual and communication gap that exists between those undertaking research and statisticians.
• Non-mathematical approach • Computer output of all examples • Comparison between software packages
Preface; 1. Introduction; 2. Basic principles behind multilevel analysis; 3. What do we gain by applying multilevel analysis?; 4. Multilevel analysis with different outcome variables; 5. Multilevel modelling; 6. Multilevel analysis in longitudinal studies; 7. Multivariate multilevel analysis; 8. Sample size calculations in multilevel studies; 9. Software for multilevel analysis; References; Index.
'… a concise practical guide for non-mathematical researchers beginning to use this technique in their work.' Pradeep Malakar, Institute Food Research