Overview

Written especially for psychometricians, scale developers, and practitioners interested in applications of Bayesian estimation and model checking of item response theory (IRT) models, this book teaches you how to accomplish all of this with the SAS MCMC Procedure. Working through this book's examples, you will learn how to write the PROC MCMC programming code to estimate various simple and more complex item response theory models, including the choice and specification of prior distributions, specification of the likelihood model, and interpretation of results. Numerous programs for conducting these analyses are provided and annotated so that you can easily modify them for your applications.

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9781629596501

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Clement A. Stone is a professor in the Research Methodology program at the University of Pittsburgh School of Education. He is an expert in psychometrics, including educational and psychological instrument development and validation, item response theory (IRT) models and applications, and Bayesian analysis of IRT models. Also an expert in SAS software, he has used SAS extensively in research utilizing simulation methods, and he instructs graduate students in the use of SAS. He applies IRT in the development and validation of educational, psychological, and behavioral assessments, including a research focus on educational achievement, critical thinking, psychosocial stress, communication outcomes, risk factors for addiction, and physical disability. He has published numerous articles, and he coauthored a chapter on the development and analysis of performance assessments in Educational Measurement. In addition to publishing in and reviewing for numerous prominent journals, he has served on the editorial boards for the Journal of Educational Measurement, Applied Measurement in Education, Educational and Psychological Measurement, and the American Educational Research Journal. Stone holds a Ph.D. in research methods, measurement, and statistics from the University of Arizona.

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