Download or read book Bayesian Item Fit Analysis for Dichotomous Item Response Theory Models written by Sandip Sinharay and published by . This book was released on 2003 with total page 47 pages. Available in PDF, EPUB and Kindle. Book excerpt:

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 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 BAYESIAN MODEL CHECKING METHODS FOR DICHOTOMOUS ITEM RESPONSE THEORY AND TESTLET MODELS written by Adam Combs and published by . This book was released on 2014 with total page 239 pages. Available in PDF, EPUB and Kindle. Book excerpt: The predominant model checking method used in Bayesian item response theory (IRT) models has been the posterior predictive (PP) method. In recent years, two new Bayesian model checking methods have been proposed that may be used as alternatives to the PP method. We refer to these as the prior-predictive posterior simulation (PPPS) method of Dey et al. (1998), and the pivotal discrepancy measure (PDM) method of Johnson (2007). These methods have shown to be effective in other Bayesian models, but have never been implemented with Bayesian IRT models. It is of practical interest to see if either of these two new methods will perform better than the PP method in assessing aspects of fit in an IRT model setting. In this dissertation, we compared the effectiveness of the PPPS and PDM model checking methods with the PP method in evaluating person fit in two-parameter normal ogive (2PN) IRT models, and overall model goodness-of-fit in 2PN testlet models. Two simulation studies were performed. The first study explored the performance of each method (PP, PPPS, and PDM) in assessing person fit, or the goodness-of-fit of an individual's set of test answers with the assumed Bayesian 2PN IRT model. Several classical person fit measures were employed under each method. We also introduced using the sum of squared Bayesian latent residuals as a person fit measure. Four different types of person miss-fit were taken from the literature, and response data sets were simulated with certain examinee's responses following these violations. We found that for most of the measures, the PPPS and PDM methods outperformed the PP method in detecting the examinee's response patterns simulated to be aberrant under the model. In particular, the sum of squared Bayesian latent residuals showed to be a very effective measure under the PPPS method. The second simulation study compares the performance of the PP method and the PPPS method in assessing the overall goodness-of-fit of a Bayesian 2PN IRT model fitted to data generated under a Bayesian 2PN testlet model with equal variance across testlets. Under the PP method we used three goodness-of-fit measures based on biserial correlations that were previously employed for checking the goodness-of-fit of a three-parameter logistic (3PL) IRT model to 3PL testlet data. For use under the PPPS method, we introduced three new goodness-of-fit measures which are calculated from posterior values of the item discrimination parameters. Data sets were simulated under four different values of testlet variance, ranging from very low to fairly high. Looking at the detection rates under the PP method, we saw that the measures performed very poorly in detecting a lack of fit of the 2PN IRT model for all data values of testlet variance. The detection rates of the new measures under the PPPS method showed to be higher than those under the PP method. However, the measures under the PPPS method only showed descent power in detecting lack of fit for large values of data generating testlet variance.

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 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 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 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 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 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 609 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 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 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 A Bayesian Approach to Person Fit Analysis in Item Response Theory Models written by Cornelis Adrianus Wijnandus Glas and published by . This book was released on 2001 with total page 27 pages. Available in PDF, EPUB and Kindle. Book excerpt:

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 2016-10-14 with total page 624 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 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.

Download or read book The Wiley Handbook of Psychometric Testing written by Paul Irwing and published by John Wiley & Sons. This book was released on 2018-03-14 with total page 1064 pages. Available in PDF, EPUB and Kindle. Book excerpt: A must-have resource for researchers, practitioners, and advanced students interested or involved in psychometric testing Over the past hundred years, psychometric testing has proved to be a valuable tool for measuring personality, mental ability, attitudes, and much more. The word ‘psychometrics’ can be translated as ‘mental measurement’; however, the implication that psychometrics as a field is confined to psychology is highly misleading. Scientists and practitioners from virtually every conceivable discipline now use and analyze data collected from questionnaires, scales, and tests developed from psychometric principles, and the field is vibrant with new and useful methods and approaches. This handbook brings together contributions from leading psychometricians in a diverse array of fields around the globe. Each provides accessible and practical information about their specialist area in a three-step format covering historical and standard approaches, innovative issues and techniques, and practical guidance on how to apply the methods discussed. Throughout, real-world examples help to illustrate and clarify key aspects of the topics covered. The aim is to fill a gap for information about psychometric testing that is neither too basic nor too technical and specialized, and will enable researchers, practitioners, and graduate students to expand their knowledge and skills in the area. Provides comprehensive coverage of the field of psychometric testing, from designing a test through writing items to constructing and evaluating scales Takes a practical approach, addressing real issues faced by practitioners and researchers Provides basic and accessible mathematical and statistical foundations of all psychometric techniques discussed Provides example software code to help readers implement the analyses discussed

Download or read book Advancing Human Assessment written by Randy E. Bennett and published by Springer. This book was released on 2017-10-17 with total page 717 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is open access under a CC BY-NC 2.5 license.​​ This book describes the extensive contributions made toward the advancement of human assessment by scientists from one of the world’s leading research institutions, Educational Testing Service. The book’s four major sections detail research and development in measurement and statistics, education policy analysis and evaluation, scientific psychology, and validity. Many of the developments presented have become de-facto standards in educational and psychological measurement, including in item response theory (IRT), linking and equating, differential item functioning (DIF), and educational surveys like the National Assessment of Educational Progress (NAEP), the Programme of international Student Assessment (PISA), the Progress of International Reading Literacy Study (PIRLS) and the Trends in Mathematics and Science Study (TIMSS). In addition to its comprehensive coverage of contributions to the theory and methodology of educational and psychological measurement and statistics, the book gives significant attention to ETS work in cognitive, personality, developmental, and social psychology, and to education policy analysis and program evaluation. The chapter authors are long-standing experts who provide broad coverage and thoughtful insights that build upon decades of experience in research and best practices for measurement, evaluation, scientific psychology, and education policy analysis. Opening with a chapter on the genesis of ETS and closing with a synthesis of the enormously diverse set of contributions made over its 70-year history, the book is a useful resource for all interested in the improvement of human assessment.

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.