Handbook of Item Response Theory: Volume 2: Statistical Tools

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Wim J. van der Linden (Professor Emeritus of Measurement and Data Analysis, University of Twente)

Handbook of Item Response Theory

Volume 2: Statistical Tools

Wim J. van der Linden (Professor Emeritus of Measurement and Data Analysis, University of Twente)

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English

Chapman & Hall/CRC
15 April 2019

Psychological theory & schools of thought; Psychological testing & measurement

Series: Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences

Drawing on the work of internationally acclaimed experts in the field, Handbook of Item Response Theory, Volume Two: Statistical Tools presents classical and modern statistical tools used in item response theory (IRT). While IRT heavily depends on the use of statistical tools for handling its models and applications, systematic introductions and reviews that emphasize their relevance to IRT are hardly found in the statistical literature. This second volume in a three-volume set fills this void.

Volume Two covers common probability distributions, the issue of models with both intentional and nuisance parameters, the use of information criteria, methods for dealing with missing data, and model identification issues. It also addresses recent developments in parameter estimation and model fit and comparison, such as Bayesian approaches, specifically Markov chain Monte Carlo (MCMC) methods.

Edited by: Wim J. van der Linden (Professor Emeritus of Measurement and Data Analysis University of Twente)
Imprint: Chapman & Hall/CRC
Country of Publication: United Kingdom
Dimensions: Height: 254mm, Width: 178mm,
Weight: 840g
ISBN: 9780367221041
ISBN 10: 0367221047
Series: Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences
Pages: 456
Publication Date: 15 April 2019
Audience: College/higher education , General/trade , Primary , ELT Advanced
Format: Paperback
Publisher's Status: Active

Basic Tools. Modeling Issues. Parameter Estimation. Model Fit and Comparison.

Wim J. van der Linden is a distinguished scientist and director of research innovation at Pacific Metrics Corporation. He is also a professor emeritus of measurement and data analysis at the University of Twente. He is a past president of the Psychometric Society and National Council on Measurement in Education (NCME) and a recipient of career achievement awards from NCME, Association of Test Publishers (ATP), and American Educational Research Association (AERA). His research interests include test theory, computerized adaptive testing, optimal test assembly, parameter linking, test equating, and response-time modeling as well as decision theory and its application to problems of educational decision making. Dr. van der Linden earned a PhD in psychometrics from the University of Amsterdam.

Reviews for Handbook of Item Response Theory: Volume 2: Statistical Tools

"""Based on scores in a battery of questions in Psychometrics, IRT is a paradigm for designing, analyzing, and interpreting the individual’s abilities. Volume two covers mainly probability distributions, models with intentional and nuisance parameters, information criteria, and model identification issues, among others. To read through and comprehend the contents of this volume two, one needs calculus and mathematical statistics background. There are 20 well written chapters covering a range of topics…written by experts from all continents. The references in the chapters are exhaustive and up-to-date. I enjoyed reading this book. I recommend this book highly to economists, psychometricians, sociologists, marketing researchers, statistics and computing professionals."" ~Journal of Statistical Computation and Simulation ""(...) the handbook presents a huge compendium of models which could be innovative even for specialists in IRT and related applied research. It can definitely be useful for lecturers and graduate students, researchers and practitioners in applied psycho-sociological projects. Actually, it can be useful in much wider area of research because it describes a large variety of statistical techniques valuable in estimations for many other problems beyond IRT."" ~Stan Lipovetsky in Technometrics, August 2021"