George Karabatsos, PhD

George Karabatsos' research deals with the development, improvement, and application of statistical models, especially for complex data sets. His research mainly deals with novel developments and applications of Bayesian models and related computational methods, for regression analysis, cluster analysis, psychometric item-response analysis, causal inference, meta-analysis, and order-restricted statistical inference.

Karabatsos’ work has been published in various peer-reviewed journals including the Journal of Computational and Graphical Statistics, Psychometrika, Journal of Statistical Planning and Inference, Electronic Journal of Statistics, Statistics Surveys, Statistics in Medicine, Computational Statistics and Data Analysis, Communication in Statistics: Simulation and Computation, Behavior Research Methods, British Journal of Mathematical and Statistical Psychology, Journal of Mathematical Psychology, Applied Psychological Measurement, and Research Synthesis Methods.

He has also published chapters in various books, including Handbook of Item Response Theory: Models, Statistical Tools, and Applications; Statistical Models for Equating, Scaling, and Linking; Nonparametric Bayesian Methods in Biostatistics; Bayesian Evaluation of Informative Hypotheses; and Bayesian Theory and Applications.

Karabatsos is also an author of a menu-based statistical software package, which can perform data analysis using any one of more than 100 statistical models.

Karabatsos’ work as Principal Investigator has been supported by generous grants from the National Science Foundation, The Spencer Foundation, and the National Institutes for Health. Karabatsos also served as an Associate Editor for the journals Psychometrika and Computational Statistics and Data Analysis.

For more details, see the Personal Website of George Karabatsos.

1998 - PhD, University of Chicago, Department of Education
Program in Measurement, Evaluation, and Statistical Analysis (MESA)