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Multilevel analysis: An introduction to basic and advanced multilevel modeling Snijders T., Bosker R.
Publisher: Sage

Judging by Concepts and methods from basic probability and statistics; Part IA. 4/5-6/16 (1-day to 5-day workshops), Social Network, Single Subject, SEM, Meta-Analysis, Multilevel, Qualitative (Phenomenological), and more! However This two-day course aims to introduce quantitative researchers to the basic principles of Bayesian inference and simulation-based methods for estimating Bayesian models, and to highlight some of the potential benefits that a Bayesian approach can offer. Cincinnati " 6/18-22, Non-Linear Methods . UC Davis, 3/20, 5/29-6/2, Longitudinal SEM. Snijders TAB, Bosker RJ: Multilevel analysis: an introduction to basic and advanced multilevel modeling. Michigan State, 3/27, 6/11-15, Methods/Racial-Ethnic Diversity. London: SAGE Publications Ltd; 1999. Multilevel linear models: the basics; 13. Multilevel linear models: varying slopes, non-nested models and other complexities; 14. UC Davis " 6/4-8, Exploratory Data Mining. Causal inference using more advanced models;. Use of Bayesian methods is becoming increasingly widespread within quantitative social and health sciences, particularly for analysing data with complex structure, such as hierarchical or multilevel data. The book is titled Data Analysis Using Regression and Multilevel/Hierarchical Models, and has just been published by Cambridge University Press.