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From | Stas Kolenikov <skolenik@gmail.com> |
To | statalist@hsphsun2.harvard.edu |
Subject | st: summer school at KU |
Date | Thu, 14 Apr 2011 12:16:00 -0500 |
I was asked to post the following information about summer courses at University of Kansas. Social and behavioral scientists on the list might be interested. The Center for Research Methods and Data Analysis and the Quantitative Training Program at the University of Kansas announces our 9th Annual Summer Institutes: “Stats Camps”’ Structural Equation Modeling: Foundations and Extended Applications (Todd D. Little & Noel A. Card, instructors) June 6-10, 2011 Topics will include confirmatory factor analysis, multiple-group comparisons, factorial invariance as well as extended applications such as hierarchical model and multi-trait, multi-method analyses. Multilevel Modeling: Foundations and Applications (Kristopher J. Preacher & James P. Selig, instructors) June 6-10, 2011 Topics will include the foundations and advanced applications of multilevel modeling, including plotting cross-level interaction effects and conducting multiparameter contrasts. Structural Equation Modeling: Advanced Longitudinal Modeling (Todd D. Little, instructor) June 13-17, 2011 Topics will include traditional panel designs, latent growth curve analysis, growth mixture modeling, and dynamic intra-individual modeling. Foundations of Meta-Analysis (Noel A. Card, instructor) June 13-17, 2011 This course teaches the skills necessary to conduct and write publishable meta-analytic reviews, including methods of searching the empirical literature, coding effect sizes, and analyzing effect sizes across multiple studies. Categorical Data Analysis (Pascal R. Deboeck & Carol M. Woods, instructors) June 13-17, 2011 This course introduces the analysis of data with categorical outcomes. Topics will include categorical probability distributions, modeling binary and multi-category outcomes, and contingency table analysis. Modern Missing Data Methods (Wei Wu & Mijke Rhemtulla, instructors) June 20-24, 2011 This course covers the design and analysis issues surrounding missing data, including types of missing data, how to prevent the bad kind and plan for the good kind, best practices for dealing with missing data, including multiple imputation and maximum likelihood approaches, and advanced statistical issues such as corrections for nonnormality and other assumption violations. Foundations of Statistical Analysis and Data Management in R (Paul E. Johnson & Pascal R. Deboeck, instructors) June 20-24, 2011 An introduction to R, the rapidly growing free software for scientific research. Along with the foundations, the following special topics are considered: the generalized linear regression model, structural equation modeling, importation of data (e.g., the General Social Survey), and the management of missing data (multiple imputation). Foundations of Test Development and Validation (Carol M. Woods, instructor) June 20-24, 2011 Course begins with how to write a test, covering principles and procedures of classical test theory, then emphasizes statistical analysis for measurement invariance (i.e., differential item functioning) and other modern approaches for item analysis including categorical factor analysis and item response theory. Social Network Analysis (Christian E. G. Steglich, instructor) June 20-24, 2011 This course covers longitudinal Social Network Analysis with the software package, SIENA. With a longitudinal focus, the course will emphasize the actor-based approach to social network analysis as implemented in SIENA. -- Stas Kolenikov, also found at http://stas.kolenikov.name Small print: I use this email account for mailing lists only. * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/