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.
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 ...
Highlights of the second edition include: Two new chapters—one on multilevel models for ordinal and count data (Ch. 7) and another on multilevel survival analysis (Ch. 8).
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 ...
Multilevel Analysis of Educational Data Bayesian methods Empirical Bayes Generalized least squares Profile likelihoods E-M algorithm Fisher scoring procedures Both educational and social science applications
Highlights of the second edition include: Two new chapters—one on multilevel models for ordinal and count data (Ch. 7) and another on multilevel survival analysis (Ch. 8).
This book provides a broad overview of basic multilevel modeling issues and illustrates techniques building analyses around several organizational data sets.
This is a practical introduction to multilevel analysis suitable for all those doing research.
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.