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.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
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
1
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
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