Explanatory Item Response Models

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Explanatory Item Response Models
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Author : Paul de Boeck
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-09
Explanatory Item Response Models written by Paul de Boeck and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-09 with Social Science categories.
This edited volume gives a new and integrated introduction to item re sponse models (predominantly used in measurement applications in psy chology, education, and other social science areas) from the viewpoint of the statistical theory of generalized linear and nonlinear mixed models. Moreover, this new framework aHows the domain of item response mod els to be co-ordinated and broadened to emphasize their explanatory uses beyond their standard descriptive uses. The basic explanatory principle is that item responses can be modeled as a function of predictors of various kinds. The predictors can be (a) char acteristics of items, of persons, and of combinations of persons and items; they can be (b) observed or latent (of either items or persons); and they can be (c) latent continuous or latent categorical. Thus, a broad range of models can be generated, including a wide range of extant item response models as weH as some new ones. Within this range, models with explana tory predictors are given special attention, but we also discuss descriptive models. Note that the 'item responses' that we are referring to are not just the traditional 'test data,' but are broadly conceived as categorical data from a repeated observations design. Hence, data from studies with repeated-observations experimental designs, or with longitudinal designs, mayaIso be modeled. The intended audience for this volume is rather broad.
Bayesian Item Response Modeling
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Author : Jean-Paul Fox
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-05-19
Bayesian Item Response Modeling written by Jean-Paul Fox and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-05-19 with Social Science categories.
The modeling of item response data is governed by item response theory, also referred to as modern test theory. The eld of inquiry of item response theory has become very large and shows the enormous progress that has been made. The mainstream literature is focused on frequentist statistical methods for - timating model parameters and evaluating model t. However, the Bayesian methodology has shown great potential, particularly for making further - provements in the statistical modeling process. The Bayesian approach has two important features that make it attractive for modeling item response data. First, it enables the possibility of incorpor- ing nondata information beyond the observed responses into the analysis. The Bayesian methodology is also very clear about how additional information can be used. Second, the Bayesian approach comes with powerful simulation-based estimation methods. These methods make it possible to handle all kinds of priors and data-generating models. One of my motives for writing this book is to give an introduction to the Bayesian methodology for modeling and analyzing item response data. A Bayesian counterpart is presented to the many popular item response theory books (e.g., Baker and Kim 2004; De Boeck and Wilson, 2004; Hambleton and Swaminathan, 1985; van der Linden and Hambleton, 1997) that are mainly or completely focused on frequentist methods. The usefulness of the Bayesian methodology is illustrated by discussing and applying a range of Bayesian item response models.
A Course In Item Response Theory And Modeling With Stata
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Author : Tenko Raykov
language : en
Publisher:
Release Date : 2018
A Course In Item Response Theory And Modeling With Stata written by Tenko Raykov and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with Item reponse modeling categories.
Over the past several decades, item response theory (IRT) and item response modeling (IRM) have become increasingly popular in the behavioral, educational, social, business, marketing, clinical, and health sciences. In this book, Raykov and Marcoulides begin with a nontraditional approach to IRT and IRM that is based on their connections to classical test theory, (nonlinear) factor analysis, generalized linear modeling, and logistic regression. Application-oriented discussions follow next. These cover the one-, two-, and three-parameter logistic models, polytomous item response models (with nominal or ordinal items), item and test information functions, instrument construction and development, hybrid models, differential item functioning, and an introduction to multidimensional IRT and IRM. The pertinent analytic and modeling capabilities of Stata are thoroughly discussed, highlighted, and illustrated on empirical examples from behavioral and social research.
Item Response Theory For Psychologists
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Author : Susan E. Embretson
language : en
Publisher: Psychology Press
Release Date : 2013-09-05
Item Response Theory For Psychologists written by Susan E. Embretson and has been published by Psychology Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-09-05 with Psychology categories.
This book develops an intuitive understanding of IRT principles through the use of graphical displays and analogies to familiar psychological principles. It surveys contemporary IRT models, estimation methods, and computer programs. Polytomous IRT models are given central coverage since many psychological tests use rating scales. Ideal for clinical, industrial, counseling, educational, and behavioral medicine professionals and students familiar with classical testing principles, exposure to material covered in first-year graduate statistics courses is helpful. All symbols and equations are thoroughly explained verbally and graphically.
Multidimensional Item Response Theory
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Author : M.D. Reckase
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-07-07
Multidimensional Item Response Theory written by M.D. Reckase and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-07-07 with Social Science categories.
Multidimensional Item Response Theory is the first book to give thorough coverage to this emerging area of psychometrics. The book describes the commonly used multidimensional item response theory (MIRT) models and the important methods needed for their practical application. These methods include ways to determine the number of dimensions required to adequately model data, procedures for estimating model parameters, ways to define the space for a MIRT model, and procedures for transforming calibrations from different samples to put them in the same space. A full chapter is devoted to methods for multidimensional computerized adaptive testing. The text is appropriate for an advanced course in psychometric theory or as a reference work for those interested in applying MIRT methodology. A working knowledge of unidimensional item response theory and matrix algebra is assumed. Knowledge of factor analysis is also helpful.
A Short Guide To Item Response Theory Models
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Author : Gerhard Tutz
language : en
Publisher: Springer Nature
Release Date : 2025-08-02
A Short Guide To Item Response Theory Models written by Gerhard Tutz and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-08-02 with Mathematics categories.
This book presents foundational concepts, essential principles, and practical applications of Item Response Theory (IRT). It provides a structured survey of diverse models that have been put forth, emphasizing both their differences and commonalities. The main focus is on modern latent trait theory models which provide measurement tools that clearly separate between person abilities and item parameters. The topics covered include the binary Rasch model, its extensions and alternative binary models, ordinal models and their extensions that account for response styles, the thresholds model, classical test theory, response models for count data, differential item functioning, and explanatory item response models. Tree-based item response models, typically not found in classical IRT textbooks, are also addressed. Applications of the models are illustrated on several data sets from differing areas, showing how models can be fitted and compared. All examples have been computed using R. Code snippets are provided, and the full R code for most of the examples is available online. The book is aimed at graduate students, applied statisticians, and researchers working in psychometrics, educators, and anyone curious about modeling strategies that enhance the precision and validity of their measurement tools. It serves as an introductory guide for beginners while also providing a resource for those seeking an overview of the plethora of available IRT models.
The Basics Of Item Response Theory Using R
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Author : Frank B. Baker
language : en
Publisher: Springer
Release Date : 2017-04-25
The Basics Of Item Response Theory Using R written by Frank B. Baker and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-04-25 with Social Science categories.
This graduate-level textbook is a tutorial for item response theory that covers both the basics of item response theory and the use of R for preparing graphical presentation in writings about the theory. Item response theory has become one of the most powerful tools used in test construction, yet one of the barriers to learning and applying it is the considerable amount of sophisticated computational effort required to illustrate even the simplest concepts. This text provides the reader access to the basic concepts of item response theory freed of the tedious underlying calculations. It is intended for those who possess limited knowledge of educational measurement and psychometrics. Rather than presenting the full scope of item response theory, this textbook is concise and practical and presents basic concepts without becoming enmeshed in underlying mathematical and computational complexities. Clearly written text and succinct R code allow anyone familiar with statistical concepts to explore and apply item response theory in a practical way. In addition to students of educational measurement, this text will be valuable to measurement specialists working in testing programs at any level and who need an understanding of item response theory in order to evaluate its potential in their settings.
Handbook Of Item Response Theory Modeling
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Author : Steven P. Reise
language : en
Publisher: Routledge
Release Date : 2014-11-20
Handbook Of Item Response Theory Modeling written by Steven P. Reise and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-20 with Psychology categories.
Item response theory (IRT) has moved beyond the confines of educational measurement into assessment domains such as personality, psychopathology, and patient-reported outcomes. Classic and emerging IRT methods and applications that are revolutionizing psychological measurement, particularly for health assessments used to demonstrate treatment effectiveness, are reviewed in this new volume. World renowned contributors present the latest research and methodologies about these models along with their applications and related challenges. Examples using real data, some from NIH-PROMIS, show how to apply these models in actual research situations. Chapters review fundamental issues of IRT, modern estimation methods, testing assumptions, evaluating fit, item banking, scoring in multidimensional models, and advanced IRT methods. New multidimensional models are provided along with suggestions for deciding among the family of IRT models available. Each chapter provides an introduction, describes state-of-the art research methods, demonstrates an application, and provides a summary. The book addresses the most critical IRT conceptual and statistical issues confronting researchers and advanced students in psychology, education, and medicine today. Although the chapters highlight health outcomes data the issues addressed are relevant to any content domain. The book addresses: IRT models applied to non-educational data especially patient reported outcomes Differences between cognitive and non-cognitive constructs and the challenges these bring to modeling. The application of multidimensional IRT models designed to capture typical performance data. Cutting-edge methods for deriving a single latent dimension from multidimensional data A new model designed for the measurement of constructs that are defined on one end of a continuum such as substance abuse Scoring individuals under different multidimensional IRT models and item banking for patient-reported health outcomes How to evaluate measurement invariance, diagnose problems with response categories, and assess growth and change. Part 1 reviews fundamental topics such as assumption testing, parameter estimation, and the assessment of model and person fit. New, emerging, and classic IRT models including modeling multidimensional data and the use of new IRT models in typical performance measurement contexts are examined in Part 2. Part 3 reviews the major applications of IRT models such as scoring, item banking for patient-reported health outcomes, evaluating measurement invariance, linking scales to a common metric, and measuring growth and change. The book concludes with a look at future IRT applications in health outcomes measurement. The book summarizes the latest advances and critiques foundational topics such a multidimensionality, assessment of fit, handling non-normality, as well as applied topics such as differential item functioning and multidimensional linking. Intended for researchers, advanced students, and practitioners in psychology, education, and medicine interested in applying IRT methods, this book also serves as a text in advanced graduate courses on IRT or measurement. Familiarity with factor analysis, latent variables, IRT, and basic measurement theory is assumed.
Handbook Of Item Response Theory
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Author : Wim J. van der Linden
language : en
Publisher: CRC Press
Release Date : 2018-02-19
Handbook Of Item Response Theory written by Wim J. van der Linden and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-02-19 with Mathematics categories.
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.
The Theory And Practice Of Item Response Theory
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Author : R. J. de Ayala
language : en
Publisher: Guilford Publications
Release Date : 2022-04-29
The Theory And Practice Of Item Response Theory written by R. J. de Ayala and has been published by Guilford Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-04-29 with Business & Economics categories.
Introduction to measurement -- The one-parameter model -- Joint maximum likelihood parameter estimation -- Marginal maximum likelihood parameter estimation -- The two-parameter model -- The three-parameter model -- Rasch models for ordered polytomous data -- Non-Rasch models for ordered polytomous data -- Models for nominal polytomous data -- Models for multidimensional data -- Linking and equating -- Differential item functioning -- Multilevel IRT models.