Download or read book Bayesian Item Response Modeling written by Jean-Paul Fox and published by Springer Science & Business Media. This book was released on 2010-05-19 with total page 323 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Bayesian Item Response Theory Methods and Applications written by Yang Liu and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Item response theory (IRT) models play a critical role in psychometric studies for the design and analysis of examinations. IRT models mainly consider the relationship among the correctness of items, individual's latent ability, difficulty of each item and other potential factors such as guessing. In this dissertation, we develop Bayesian modeling methods and model selection techniques under the IRT model framework. For Bayesian model comparison, the Bayes factor is a widely used tool, which requires computation of the marginal likelihoods. For complex models such as the IRT models, the marginal likelihoods are not analytically available. There are a variety of Monte Carlo methods for estimating or computing the marginal likelihoods, though some of them may not be feasible for IRT models due to the high dimensionality of the parameter space. We review several different Monte Carlo methods for marginal likelihood computation under classic IRT models, develop the "best'' implementation of these methods for the IRT models, and apply these methods to a real dataset for comparison of the classic one-parameter IRT model and two-parameter IRT model. With increasing availability of computerized testing, observations are often collected at irregular and variable time points. We adopt a dynamic IRT model based on the one-parameter IRT model to accommodate this data structure. A hierarchical layer on the dynamic IRT model is built to capture the relationship between the "growth factor" and the characteristics of individuals. We use the Bayes factor to perform variable selection on the covariates linked to the growth, and develop a Monte Carlo approach to compute the Bayes factors for all model pairs using a single Markov chain Monte Carlo (MCMC) output. We also show the model selection consistency of the Bayes factor under certain conditions. Additionally, to allow more flexibility, we propose a nonparametric model and embed a monotone shape constraint on the mean latent growth trend. Further, we develop a partially collapsed Gibbs sampling algorithm coupled with a reversible jump MCMC technique to sample the dimension-varying parameters from their corresponding posterior distribution.
Download or read book Item Response Theory written by Ronald K. Hambleton and published by Springer Science & Business Media. This book was released on 2013-11-11 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Handbook of Modern Item Response Theory written by Wim J. van der Linden and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 509 pages. Available in PDF, EPUB and Kindle. Book excerpt: Item response theory has become an essential component in the toolkit of every researcher in the behavioral sciences. It provides a powerful means to study individual responses to a variety of stimuli, and the methodology has been extended and developed to cover many different models of interaction. This volume presents a wide-ranging handbook to item response theory - and its applications to educational and psychological testing. It will serve as both an introduction to the subject and also as a comprehensive reference volume for practitioners and researchers. It is organized into six major sections: the nominal categories model, models for response time or multiple attempts on items, models for multiple abilities or cognitive components, nonparametric models, models for nonmonotone items, and models with special assumptions. Each chapter in the book has been written by an expert of that particular topic, and the chapters have been carefully edited to ensure that a uniform style of notation and presentation is used throughout. As a result, all researchers whose work uses item response theory will find this an indispensable companion to their work and it will be the subject's reference volume for many years to come.
Download or read book Fundamentals of Item Response Theory written by Ronald K. Hambleton and published by SAGE Publications. This book was released on 1991-07-23 with total page 185 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Handbook of Item Response Theory written by Wim J. van der Linden and published by CRC Press. This book was released on 2018-02-19 with total page 1584 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Handbook of Item Response Theory Volume Two written by Wim J. van der Linden and published by CRC Press. This book was released on 2016-03-29 with total page 487 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Bayesian Analysis of Item Response Theory Models Using SAS written by Clement A. Stone and published by Sas Inst. This book was released on 2015-03-01 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written especially for psychometricians, scale developers, and practitioners interested in applications of Bayesian estimation and model checking of item response theory (IRT) models, this book teaches you how to accomplish all of this with the SAS MCMC Procedure, Because of its tutorial structure, Bayesian Analysis of Item Response Theory Models Using SAS will be of immediate practical use to SAS users with some introductory background in IRT models and the Bayesian paradigm. Working through this book's examples, you will learn how to write the PROC MCMC programming code to estimate various simple and more complex IRT models, including the choice and specification of prior distributions, specification of the likelihood model, and interpretation of results. Specifically, you will learn PROC MCMC programming code for estimating particular models and ways to interpret results that illustrate convergence diagnostics and inferences for parameters, as well as results that can be used by scale developers—for example, the plotting of item response functions. In addition, you will learn how to compare competing IRT models for an application, as well as evaluate the fit of models with the use of posterior predictive model checking methods. Numerous programs for conducting these analyses are provided and annotated so that you can easily modify them for your applications.
Download or read book Handbook of Item Response Theory written by Wim J. van der Linden and published by CRC Press. This book was released on 2017-12-15 with total page 722 pages. Available in PDF, EPUB and Kindle. Book excerpt: Drawing on the work of internationally acclaimed experts in the field, Handbook of Item Response Theory, Volume 3: Applications presents applications of item response theory to practical testing problems. While item response theory may be known primarily for its advances in theoretical modeling of responses to test items, equal progress has been made in its providing innovative solutions to daily testing problems. This third volume in a three-volume set highlights the major applications. Specifically, this volume covers applications to test item calibration, item analysis, model fit checking, test-score interpretation, optimal test design, adaptive testing, standard setting, and forensic analyses of response data. It describes advances in testing in areas such as large-scale educational assessment, psychological testing, health measurement, and measurement of change. In addition, it extensively reviews computer programs available to run any of the models and applications in Volume One and Three. Features Includes contributions from internationally acclaimed experts with a history of advancing applications of item response theory Provides extensive cross-referencing and common notation across all chapters in this three-volume set Underscores the importance of treating each application in a statistically rigorous way Reviews major computer programs for item response theory analyses and applications. Wim J. van der Linden is a distinguished scientist and director of research and innovation at Pacific Metrics Corporation. Dr. van der Linden is also a professor emeritus of measurement and data analysis at the University of Twente. His research interests include test theory, adaptive testing, optimal test assembly, parameter linking, test equating, and response-time modeling as well as decision theory and its applications to problems of educational decision making.
Download or read book Bayesian Analysis of Item Response Theory and Its Applications to Longitudinal Education Data written by Abhisek Saha and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Inferences on ability in item response theory (IRT) have been mainly based on item responses while response time is often ignored. This is a loss of information especially with the advent of computerized tests. Most of the IRT models may not apply to these modern computerized tests as they still suffer from at least one of the three problems, local independence, randomized item and individually varying test dates, due to the flexibility and complex designs of computerized (adaptive) tests. In Chapter 2, we propose a new class of state space models, namely dynamic item responses and response times models (DIR-RT models), which conjointly model response time with time series of dichotomous responses. It aims to improve the accuracy of ability estimation via auxilary information from response time. A simulation study is conducted to ensure correctness of proposed sampling schemes to estimate parameters, whereas an empirical study is conducted using MetaMetrics datasets to demonstrate its implications in practice. In Chapter 3, we have investigated the difficulty in implementing the standard model diagnostic methods while comparing two popular response time models (i.e., monotone and inverted U-shape). A new variant of conditional deviance information criterion (DIC) is proposed and some simulation studies are conducted to check its performance. The results of model comparison support the inverted U shaped model, as discussed in Chapter 1, which can better capture examinees' behaviors and psychology in exams. The estimates of ability via Dynamic Item Response models (DIR) or DIR-RT model often are non-monotonic and zig-zagged because of irregularly spaced time-points though the inherent mean ability growth process is monotonic and smooth. Also the parametric assumption of ability process may not be always exact. To have more flexible yet smooth and monotonic estimates of ability we propose a semi-parametric dynamic item response model and study the robustness of the proposed model. Finally, as every student’s growth is different from others, it may be of importance to identify groups of fast learners from slow learners. The growth curves are clustered into distinct groups based on learning rates. A spline derivative based clustering method is suggested in light of its efficacy on some simulated data in Chapter 5 as part of future works.
Download or read book Multidimensional Item Response Theory written by M.D. Reckase and published by Springer Science & Business Media. This book was released on 2009-07-07 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: First thorough treatment of multidimensional item response theory Description of methods is supported by numerous practical examples Describes procedures for multidimensional computerized adaptive testing
Download or read book Handbook of Polytomous Item Response Theory Models written by Michael Nering and published by Taylor & Francis. This book was released on 2011-01-19 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive Handbook focuses on the most used polytomous item response theory (IRT) models. These models help us understand the interaction between examinees and test questions where the questions have various response categories. The book reviews all of the major models and includes discussions about how and where the models originated, conceptually and in practical terms. Diverse perspectives on how these models can best be evaluated are also provided. Practical applications provide a realistic account of the issues practitioners face using these models. Disparate elements of the book are linked through editorial sidebars that connect common ideas across chapters, compare and reconcile differences in terminology, and explain variations in mathematical notation. These sidebars help to demonstrate the commonalities that exist across the field. By assembling this critical information, the editors hope to inspire others to use polytomous IRT models in their own research so they too can achieve the type of improved measurement that such models can provide. Part 1 examines the most commonly used polytomous IRT models, major issues that cut across these models, and a common notation for calculating functions for each model. An introduction to IRT software is also provided. Part 2 features distinct approaches to evaluating the effectiveness of polytomous IRT models in various measurement contexts. These chapters appraise evaluation procedures and fit tests and demonstrate how to implement these procedures using IRT software. The final section features groundbreaking applications. Here the goal is to provide solutions to technical problems to allow for the most effective use of these models in measuring educational, psychological, and social science abilities and traits. This section also addresses the major issues encountered when using polytomous IRT models in computerized adaptive testing. Equating test scores across different testing contexts is the focus of the last chapter. The various contexts include personality research, motor performance, health and quality of life indicators, attitudes, and educational achievement. Featuring contributions from the leading authorities, this handbook will appeal to measurement researchers, practitioners, and students who want to apply polytomous IRT models to their own research. It will be of particular interest to education and psychology assessment specialists who develop and use tests and measures in their work, especially researchers in clinical, educational, personality, social, and health psychology. This book also serves as a supplementary text in graduate courses on educational measurement, psychometrics, or item response theory.
Download or read book Handbook of Item Response Theory written by Wim J. van der Linden and published by CRC Press. This book was released on 2017-03-31 with total page 493 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Handbook of Item Response Theory Modeling written by Steven P. Reise and published by Routledge. This book was released on 2014-11-20 with total page 710 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Improving Motor Carrier Safety Measurement written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2017-10-01 with total page 183 pages. Available in PDF, EPUB and Kindle. Book excerpt: Every year roughly 100,000 fatal and injury crashes occur in the United States involving large trucks and buses. The Federal Motor Carrier Safety Administration (FMCSA) in the U.S. Department of Transportation works to reduce crashes, injuries, and fatalities involving large trucks and buses. FMCSA uses information that is collected on the frequency of approximately 900 different violations of safety regulations discovered during (mainly) roadside inspections to assess motor carriers' compliance with Federal Motor Carrier Safety Regulations, as well as to evaluate their compliance in comparison with their peers. Through use of this information, FMCSA's Safety Measurement System (SMS) identifies carriers to receive its available interventions in order to reduce the risk of crashes across all carriers. Improving Motor Carrier Safety Measurement examines the effectiveness of the use of the percentile ranks produced by SMS for identifying high-risk carriers, and if not, what alternatives might be preferred. In addition, this report evaluates the accuracy and sufficiency of the data used by SMS, to assess whether other approaches to identifying unsafe carriers would identify high-risk carriers more effectively, and to reflect on how members of the public use the SMS and what effect making the SMS information public has had on reducing crashes.
Download or read book Item Response Theory written by Christine DeMars and published by Oxford University Press. This book was released on 2010-04-30 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a title in our Understanding Statistics series, which is designed to provide researchers with authoritative guides to understanding, presenting and critiquing analyses and associated inferences. Each volume in the series demonstrates how the relevant topic should be reported -- including detail surrounding what can be said, and how it should be said, as well as drawing boundaries around what cannot appropriately be claimed or inferred. This volume addresses an important issue for the design of survey instruments, which is rarely taught in graduate programs beyond those specifically for statisticians. Item Response Theory is used to describe the application of mathematical models to data from questionnaires and tests as a basis for measuring abilities, attitudes, or other variables. It is used for statistical analysis and development of assessments, often for high stakes tests such as the Graduate Record Examination. The author is known for her clear, accessible writing; like all books in this series, this volume includes examples of both good and bad write-ups for methods sections of journal articles.
Download or read book Explanatory Item Response Models written by Paul de Boeck and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited volume gives a new and integrated introduction to item response models (predominantly used in measurement applications in psychology, education, and other social science areas) from the viewpoint of the statistical theory of generalized linear and nonlinear mixed models. It also includes a chapter on the statistical background and one on useful software.
