Applauded for its clarity, this accessible introduction helps readers apply multilevel techniques to their research. The book also includes advanced extensions, making it useful as both an introduction for students and as a reference for researchers. Basic models and examples are discussed in nontechnical terms with an emphasis on understanding the methodological and statistical issues involved in using these models. The estimation and interpretation of multilevel models is demonstrated using realistic examples from various disciplines including psychology, education, public health, and sociology. Readers are introduced to a general framework on multilevel modeling which covers both observed and latent variables in the same model, while most other books focus on observed variables. In addition, Bayesian estimation is introduced and applied using accessible software.
... controlling for variable X. It is analogous to the usual intraclass correlation coefficient , but now controlling for X. The formula for the ( non - residual , or raw ) intraclass correlation coefficient was just the same ...
An Introduction to Basic and Advanced Multilevel Modeling Tom A B Snijders, Roel J Bosker ... Stapleton, L. (2002) 'The incorporation of sample weights into multilevel structural equation models'. Structural Equation Modeling ...
This open access book is a practical introduction to multilevel modelling or multilevel analysis (MLA) - a statistical technique being increasingly used in public health and health services research.
... in National Bureau of Standards Applied Mathematics Series. U.S. Government Printing Office, Washington, DC, 1964. 3. M. Aitkin, D. Anderson, B. Francis, and J. Hinde. Statistical Modelling in GLIM. Clarendon Press, Oxford, 1989. 4 ...
The intervention for low - birth - weight children is described by Brooks - Gunn , Liaw , and Klebanov ( 1992 ) and Hill , Brooks - Gunn , and Waldfogel ( 2003 ) . Imbalance plots such as Figure 10.3 are commonly used ; see Hansen ...
This book provides a uniquely accessible introduction to multilevel modeling, a powerful tool for analyzing relationships between an individual-level dependent variable, such as student reading achievement, and individual-level and ...
This new handbook is the definitive resource on advanced topics related to multilevel analysis.
This book provides a broad overview of basic multilevel modeling issues and illustrates techniques building analyses around several organizational data sets.
In T. D. Little, K. U. Schnabel, & J. Baumert (Eds.), Modeling longitudinal and multilevel data (pp. ... Sample size requirements for 2-level designs in educational research. ... Complex sample data in structural equation modeling.
Multilevel Analysis of Educational Data focuses on the principles and procedures used in the evaluation of educational progress. The selection first offers information on some applications of multilevel models to...