Multilevel Analysis: An Introduction to Basic and Advanced Multilevel Modeling

Voorkant
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.
 

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Inhoudsopgave

Introduction
1
Multilevel Theories Multistage Sampling and Multilevel Models
6
Statistical Treatment of Clustered Data
13
The Random Intercept Model
38
The Hierarchical Linear Model
67
Testing and Model Specification
86
How Much Does the Model Explain?
99
Heteroscedasticity
110
Designing Multilevel Studies
140
Crossed Random Coefficients
155
Longitudinal Data
166
Multivariate Multilevel Models
200
Discrete Dependent Variables
207
Software
239
References
252
Index
261

Assumptions of the Hierarchical Linear Model
120

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Pagina 254 - Random effects probit and logistic regression models for three-level data'.
Pagina 13 - The simplest way to do this is to work with the averages for each macro-unit. There is nothing wrong with aggregation...

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