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Society of Multivariate Experimental Psychology
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Dr. Jonathan Templin

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Wed, 06/11/2014 - 11:15 by Dr. Jonathan Templin

Professor and E. F. Lindquist Chair
Website: 
Email: 
jonathan-templin@uiowa.edu

Jonathan Templin is Professor and E. F. Lindquist Chair in the Department of Psychological and Quantitative Foundations at the University of Iowa. He a member of the Educational Measurement and Statistics Program. Dr. Templin received his Ph.D. in Quantitative Psychology at the University of Illinois at Urbana-Champaign in 2004, where he also received an M.S. in Statistics. He joined the faculty of the University of Iowa in January, 2019, after stints on the faculty at the University of Kansas, the University of Nebraska-Lincoln, and the University of Georgia. The main focus of Dr. Templin's research is in the field of diagnostic classification models—psychometric models that seek to provide multiple reliable scores from educational and psychological assessments. He also studies Bayesian statistics, as applied in psychometrics, broadly. Dr. Templin’s research program has been funded by the United States National Science Foundation and Institute of Education Sciences and has been published in journals such as Psychometrika, Psychological Methods, Applied Psychological Measurement, and the Journal of Educational Measurement. Dr. Templin is currently co-editor of the Journal of Educational Measurement and Associate Editor for Psychometrika. He is coauthor of the book Diagnostic Measurement: Theory, Methods, and Applications, which won the 2012 American Educational Research Association Division D Award for Significant Contribution to Educational Measurement and Research Methodology. He is the winner of the 2015 AERA Cognition and Assessment SIG Award for Outstanding Contribution to Research in Cognition and Assessment and the inaugural 2017 Robert Linn Lecture Award.

Expertise and Interest Areas: 
Bayesian Modeling
Diagnostic Classification Modeling
Generalized multilevel (mixed, hierarchical linear) models
Item Response Theory Modeling
Latent Class Analysis
Latent Profile Analysis
Markov Chain Monte Carlo Methods
Measurement
Mixture Modeling
Multivariate Analysis
Statistical Inference
Statistical Learning
Structural Equation Modeling
Test Theory

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