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Table of contents:
The main methods, techniques and issues for carrying out multilevel modeling and analysis are covered in this book. The book is an applied introduction to the topic, providing a clear conceptual understanding of the issues involved in multilevel analysis and will be a useful reference tool. Information on designing multilevel studies, sampling, testing and model specification and interpretation of models is provided. A comprehensive guide to the software available is included. Multilevel Analysis is the ideal guide for researchers and applied statisticians in the social sciences, including education, but will also interest researchers in economics, and biological, medical and health disciplines.
Contents:
Introduction Multilevel Theories, Multi-Stage Sampling and Multilevel Models Statistical Treatment of Clustered Data The Random Intercept Model The Hierarchical Linear Model Testing and Model Specification How Much Does the Model Explain? Heteroscedasticity Assumptions of the Hierarchical Linear Model Designing Multilevel Studies Crossed Random Coefficients Longitudinal Data Multivariate Multilevel Models Discrete Dependent Variables Software
Brief Description:
This text covers the main methods, techniques and issues for carrying out multilevel modelling and analysis. It provides information on designing multilevel studies, sampling, testing, model specification and interpreting the models. A comprehensive guide to the statistical software is included.
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