1st Edition

Handbook of Item Response Theory Three Volume Set

    1500 Pages
    by Chapman & Hall

    1500 Pages 200 B/W Illustrations
    by Chapman & Hall

    1500 Pages 200 B/W Illustrations
    by Chapman & Hall

    Drawing on the work of 75 internationally acclaimed experts in the field, Handbook of Item Response Theory, Three-Volume Set presents all major item response models, classical and modern statistical tools used in item response theory (IRT), and major areas of applications of IRT in educational and psychological testing, medical diagnosis of patient-reported outcomes, and marketing research. It also covers CRAN packages, WinBUGS, Bilog MG, Multilog, Parscale, IRTPRO, Mplus, GLLAMM, Latent Gold, and numerous other software tools.

    A full update of editor Wim J. van der Linden and Ronald K. Hambleton’s classic Handbook of Modern Item Response Theory, this handbook has been expanded from 28 chapters to 85 chapters in three volumes. The three volumes are thoroughly edited and cross-referenced, with uniform notation, format, and pedagogical principles across all chapters. Each chapter is self-contained and deals with the latest developments in IRT.

    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

    Basic Tools
    Logit, Probit, and Other Response Functions
    James H. Albert
    Discrete Distributions
    Jodi M. Casabianca and Brian W. Junker
    Multivariate Normal Distribution
    Jodi M. Casabianca and Brian W. Junker
    Exponential Family Distributions Relevant to IRT
    Shelby J. Haberman
    Loglinear Models for Observed-Score Distributions
    Tim Moses
    Distributions of Sums of Nonidentical Random Variables
    Wim J. van der Linden
    Information Theory and Its Application to Testing
    Hua-Hua Chang, Chun Wang, and Zhiliang Ying

    Modeling Issues
    Identification of Item Response Theory Models
    Ernesto San Martín
    Models with Nuisance and Incidental Parameters
    Shelby J. Haberman
    Missing Responses in Item Response Modeling
    Robert J. Mislevy

    Parameter Estimation
    Maximum-Likelihood Estimation
    Cees A. W. Glas
    Expectation Maximization Algorithm and Extensions
    Murray Aitkin
    Bayesian Estimation
    Matthew S. Johnson and Sandip Sinharay
    Variational Approximation Methods
    Frank Rijmen, Minjeong Jeon, and Sophia Rabe-Hesketh
    Markov ChainMonte Carlo for Item Response Models
    Brian W. Junker, Richard J. Patz, and Nathan M. VanHoudnos
    Statistical Optimal Design Theory
    Heinz Holling and Rainer Schwabe

    Model Fit and Comparison
    Frequentist Model-Fit Tests
    Cees A. W. Glas
    Information Criteria
    Allan S. Cohen and Sun-Joo Cho
    Bayesian Model Fit and Model Comparison
    Sandip Sinharay
    Model Fit with Residual Analyses
    Craig S. Wells and Ronald K. Hambleton

    Item Calibration and Analysis
    Item-Calibration Designs
    Martijn P.F. Berger
    Parameter Linking
    Wim J. van der Linden and Michelle D. Barrett
    Dimensionality Analysis
    Robert D. Gibbons and Li Cai
    Differential Item Functioning
    Dani Gamerman, Flávio B. Goncalves, and Tufi M. Soares
    Calibrating Technology-Enhanced Items
    Richard M. Luecht

    Person Fit and Scoring
    Person Fit
    Cees A. W. Glas and Naveed Khalid
    Score Reporting and Interpretation
    Ronald K. Hambleton and April L. Zenisky
    IRT Observed-Score Equating
    Wim J. van der Linden

    Test Design
    Optimal Test Design
    Wim J. van der Linden
    Adaptive Testing
    Wim J. van der Linden
    Standard Setting
    Daniel Lewis and Jennifer Lord-Bessen
    Test Speededness and Time Limits
    Wim J. van der Linden
    Item and Test Security
    Wim J. van der Linden

    Areas of Application
    Large-Scale Group-Score Assessments
    John Mazzeo
    Psychological Testing
    Paul De Boeck
    Cognitive Diagnostic Assessment
    Chung Wang and Hua-Hua Chang
    Health Measurement
    Richard C. Gershon, Ron D. Hays, and Michael Kallen
    Marketing Research
    Martijn G. de Jong and Ulf Böckenholt
    Measuring Change Using Rasch Models
    Gerhard H. Fischer

    Computer Programs
    IRT Packages in R
    Thomas Rusch, Patrick Mair, and Reinhold Hatzinger
    Bayesian Inference Using Gibbs Sampling (BUGS) for IRT Models
    Matthew S. Johnson
    Michele F. Zimowski
    Eiji Muraki
    Li Cai
    Xcalibre 4
    Nathan A. Thompson and Jieun Lee
    Peter M. Bentler, Eric Wu, and Patrick Mair
    ACER ConQuest
    Raymond J. Adam, Margaret L. Wu, and Mark R. Wilson
    Bengt Muthén and Linda Muthén
    Sophia Rabe-Hesketh and Anders Skrondal
    Latent GOLD
    Jeroen K. Vermunt
    Kyung (Chris) T. Han
    Seung W. Choi
    J. Patrick Meyer


    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.