Fundamentals of Item Response Theory

Fundamentals of Item Response Theory PDF Author: Ronald K. Hambleton
Publisher: SAGE
ISBN: 9780803936478
Category : Psychology
Languages : en
Pages : 192

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Book Description
By using familiar concepts from classical measurement methods and basic statistics, this book introduces the basics of item response theory (IRT) and explains the application of IRT methods to problems in test construction, identification of potentially biased test items, test equating and computerized-adaptive testing. The book also includes a thorough discussion of alternative procedures for estimating IRT parameters and concludes with an exploration of new directions in IRT research and development.

Fundamentals of Item Response Theory

Fundamentals of Item Response Theory PDF Author: Ronald K. Hambleton
Publisher: SAGE
ISBN: 9780803936478
Category : Psychology
Languages : en
Pages : 192

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Book Description
By using familiar concepts from classical measurement methods and basic statistics, this book introduces the basics of item response theory (IRT) and explains the application of IRT methods to problems in test construction, identification of potentially biased test items, test equating and computerized-adaptive testing. The book also includes a thorough discussion of alternative procedures for estimating IRT parameters and concludes with an exploration of new directions in IRT research and development.

Fundamentals of Item Response Theory

Fundamentals of Item Response Theory PDF Author: Ronald K. Hambleton
Publisher: SAGE Publications
ISBN: 1506315860
Category : Social Science
Languages : en
Pages : 185

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Book Description
Using familiar concepts from classical measurement methods and basic statistics, Hambleton and colleagues introduce the basics of item response theory (IRT) and explain the application of IRT methods to problems in test construction, identification of potentially biased test items, test equating, and computerized-adaptive testing. The book also includes a thorough discussion of alternative procedures for estimating IRT parameters, such as maximum likelihood estimation, marginal maximum likelihood estimation, and Bayesian estimation in such a way that the reader does not need any knowledge of calculus to follow these explanations. Including step-by-step numerical examples throughout, the book concludes with an exploration of new directions in IRT research and development.

Introduction to Item Response Theory Models and Applications

Introduction to Item Response Theory Models and Applications PDF Author: James Carlson
Publisher: Taylor & Francis
ISBN: 1000195325
Category : Psychology
Languages : en
Pages : 183

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Book Description
This is a highly accessible, comprehensive introduction to item response theory (IRT) models and their use in various aspects of assessment/testing. The book employs a mixture of graphics and simulated data sets to ease the reader into the material and covers the basics required to obtain a solid grounding in IRT. Written in an easily accessible way that assumes little mathematical knowledge, Carlson presents detailed descriptions of several commonly used IRT models, including those for items scored on a two-point (dichotomous) scale such as correct/incorrect, and those scored on multiple-point (polytomous) scales, such as degrees of correctness. One chapter describes a model in-depth and is followed by a chapter of instructions and illustrations showing how to apply the models to the reader’s own work. This book is an essential text for instructors and higher level undergraduate and postgraduate students of statistics, psychometrics, and measurement theory across the behavioral and social sciences, as well as testing professionals.

Item Response Theory

Item Response Theory PDF Author: Ronald K. Hambleton
Publisher: Springer Science & Business Media
ISBN: 9401719888
Category : Education
Languages : en
Pages : 340

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Book Description
In the decade of the 1970s, item response theory became the dominant topic for study by measurement specialists. But, the genesis of item response theory (IRT) can be traced back to the mid-thirties and early forties. In fact, the term "Item Characteristic Curve," which is one of the main IRT concepts, can be attributed to Ledyard Tucker in 1946. Despite these early research efforts, interest in item response theory lay dormant until the late 1960s and took a backseat to the emerging development of strong true score theory. While true score theory developed rapidly and drew the attention of leading psychometricians, the problems and weaknesses inherent in its formulation began to raise concerns. Such problems as the lack of invariance of item parameters across examinee groups, and the inadequacy of classical test procedures to detect item bias or to provide a sound basis for measurement in "tailored testing," gave rise to a resurgence of interest in item response theory. Impetus for the development of item response theory as we now know it was provided by Frederic M. Lord through his pioneering works (Lord, 1952; 1953a, 1953b). The progress in the fifties was painstakingly slow due to the mathematical complexity of the topic and the nonexistence of computer programs.

The Basics of Item Response Theory Using R

The Basics of Item Response Theory Using R PDF Author: Frank B. Baker
Publisher: Springer
ISBN: 3319542052
Category : Social Science
Languages : en
Pages : 174

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Book Description
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.

Item Response Theory

Item Response Theory PDF Author: Frank B. Baker
Publisher: CRC Press
ISBN: 9780824758257
Category : Mathematics
Languages : en
Pages : 528

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Book Description
Item Response Theory clearly describes the most recently developed IRT models and furnishes detailed explanations of algorithms that can be used to estimate the item or ability parameters under various IRT models. Extensively revised and expanded, this edition offers three new chapters discussing parameter estimation with multiple groups, parameter estimation for a test with mixed item types, and Markov chain Monte Carlo methods. It includes discussions on issues related to statistical theory, numerical methods, and the mechanics of computer programs for parameter estimation, which help to build a clear understanding of the computational demands and challenges of IRT estimation procedures.

The Theory and Practice of Item Response Theory, Second Edition

The Theory and Practice of Item Response Theory, Second Edition PDF Author: R. J. de Ayala
Publisher: Guilford Publications
ISBN: 1462547753
Category : Business & Economics
Languages : en
Pages : 674

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Book Description
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.

Item Response Theory for Psychologists

Item Response Theory for Psychologists PDF Author: Susan E. Embretson
Publisher: Psychology Press
ISBN: 9780805828184
Category : Psychology
Languages : en
Pages : 371

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Book Description
"Item Response Theory (IRT) is, increasingly, the psychometric method used for contemporary psychological tests. The goal of this book is to explain IRT. The book is especially useful to psychologists and social scientists familiar with small-scale cognitive and personality measures, of those who want to use IRT to analyze scales used in their own research. It is also useful for graduate students and practitioners who want to understand the contemporary, psychometric foundations of the tests they administer. Familiar psychological concepts are used to help explain various IRT principles. The book develops an intuitive understanding of IRT principles through its use of graphical displays and analysis of psychological principles."--Jacket.

A Course in Item Response Theory and Modeling with Stata

A Course in Item Response Theory and Modeling with Stata PDF Author: Tenko Raykov
Publisher:
ISBN: 9781597182669
Category : Item reponse modeling
Languages : en
Pages : 270

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Book Description
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.

Bayesian Item Response Modeling

Bayesian Item Response Modeling PDF Author: Jean-Paul Fox
Publisher: Springer Science & Business Media
ISBN: 1441907424
Category : Social Science
Languages : en
Pages : 323

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Book Description
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.