Handbook of Item Response Theory, Volume One: Models (Hardback) book cover

Handbook of Item Response Theory, Volume One

Models

Edited by Wim J. van der Linden

© 2016 – Chapman and Hall/CRC

595 pages | 93 B/W Illus.

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About the Book

Drawing on the work of internationally acclaimed experts in the field, Handbook of Item Response Theory, Volume One: Models presents all major item response models. This first volume in a three-volume set covers many model developments that have occurred in item response theory (IRT) during the last 20 years. It describes models for different response formats or response processes, the need of deeper parameterization due to a multilevel or hierarchical structure of the response data, and other extensions and insights.

In Volume One, all chapters have a common format with each chapter focusing on one family of models or modeling approach. An introductory section in every chapter includes some history of the model and a motivation of its relevance. Subsequent sections present the model more formally, treat the estimation of its parameters, show how to evaluate its fit to empirical data, illustrate the use of the model through an empirical example, and discuss further applications and remaining research issues.

Table of Contents

Introduction

Wim J. van der Linden

Dichotomous Models

Unidimensional Logistic Models

Wim J. van der Linden

Rasch Model

Matthias von Davier

Nominal and Ordinal Models

Nominal Categories Models

David Thissen and Li Cai

Rasch Rating Scale Model

David Andrich

Graded Response Models

Fumiko Samejima

Partial Credit Model

Geoff N. Masters

Generalized Partial Credit Model

Eiji Muraki and Mari Muraki

Sequential Models for Ordered Responses

Gerhard Tutz

Models for Continuous Responses

Gideon J. Mellenbergh

Multidimensional and Multicomponent Models

Normal-Ogive Multidimensional Models

Hariharan Swaminathan and H. Jane Rogers

Logistic Multidimensional Models

Mark D. Reckase

Linear Logistic Models

Rianne Janssen

Multicomponent Models

Susan E. Embretson

Models for Response Times

Poisson and Gamma Models for Reading Speed and Error

Margo G. H. Jansen

Lognormal Response-Time Model

Wim J. van der Linden

Diffusion-Based Response-Time Models

Francis Tuerlinckx, Dylan Molenaar, and Han L. J. van der Maas

Nonparametric Models

Mokken Models

Klaas Sijtsma and Ivo W. Molenaar

Bayesian Nonparametric Response Models

George Karabatsos

Functional Approaches to Modeling Response Data

James Ramsay

Models for Nonmonotone Items

Hyperbolic Cosine Model for Unfolding Responses

David Andrich

Generalized Graded Unfolding Model

James S. Roberts

Hierarchical Response Models

Logistic Mixture-Distribution Response Models

Matthias von Davier and Jürgen Rost

Multilevel Response Models with Covariates and Multiple Groups

Jean-Paul Fox and Cees A. W. Glas

Two-Tier Item Factor Analysis Modeling

Li Cai

Item-Family Models

Cees A. W. Glas, Wim J. van der Linden, and Hanneke Geerlings

Hierarchical Rater Models

Jodi M. Casabianca, Brian W. Junker, and Richard J. Patz

Randomized Response Models for Sensitive Measurements

Jean-Paul Fox

Joint Hierarchical Modeling of Responses and Response Times

Wim J. van der Linden and Jean-Paul Fox

Generalized Modeling Approaches

Generalized Linear Latent and Mixed Modeling

Sophia Rabe-Hesketh and Anders Skrondal

Multidimensional, Multilevel, and Multi-Timepoint Item Response Modeling

Bengt Muthén and Tihomir Asparouhov

Mixed-Coefficients Multinomial Logit Models

Raymond. J. Adams, Mark R. Wilson, and Margaret L. Wu

Explanatory Response Models

Paul De Boeck and Mark R. Wilson

About the Editor

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.

About the Series

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

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Subject Categories

BISAC Subject Codes/Headings:
MAT029000
MATHEMATICS / Probability & Statistics / General