This practical introduction helps readers apply multilevel techniques to their research. Noted as an accessible introduction, the book also includes advanced extensions, making it useful as both an introduction and as a reference to students, researchers, and methodologists. Basic models and examples are discussed in non-technical 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. For example, readers will find data sets on stress in hospitals, GPA scores, survey responses, street safety, epilepsy, divorce, and sociometric scores, to name a few. The data sets are available on the website in SPSS, HLM, MLwiN, LISREL and/or Mplus files. Readers are introduced to both the multilevel regression model and multilevel structural models. 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). Thoroughly updated chapters on multilevel structural equation modeling that reflect the enormous technical progress of the last few years. The addition of some simpler examples to help the novice, whilst the more complex examples that combine more than one problem have been retained. A new section on multivariate meta-analysis (Ch. 11). Expanded discussions of covariance structures across time and analyzing longitudinal data where no trend is expected. Expanded chapter on the logistic model for dichotomous data and proportions with new estimation methods. An updated website at http://www.joophox.net/ with data sets for all the text examples and up-to-date screen shots and PowerPoint slides for instructors. Ideal for introductory courses on multilevel modeling and/or ones that introduce this topic in some detail taught in a variety of disciplines including: psychology, education, sociology, the health sciences, and business. The advanced extensions also make this a favorite resource for researchers and methodologists in these disciplines. A basic understanding of ANOVA and multiple regression is assumed. The section on multilevel structural equation models assumes a basic understanding of SEM.
... 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 is a practical introduction to multilevel analysis suitable for all those doing research.
This book provides a broad overview of basic multilevel modeling issues and illustrates techniques building analyses around several organizational data sets.
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
... Society of London), seriesB, 186, 781–875. Krieger,N.(2000). Epidemiology andsocial sciences: towards a critical reengagement in the 21st century. Epidemiologic Reviews, 22, 155–163. Kuhn,T.S.(1972). La ... Sociological Methodology 1983–1984.