st: summer school at KU

[Stas Kolenikov <skolenik@gmail.com>]

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.

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