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First thorough treatment of multidimensional item response theory Description of methods is supported by numerous practical examples Describes procedures for multidimensional computerized adaptive testing
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.
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
This volume highlights research and conceptual insights into one of the most basic, and yet, perplexing research issues in management-handling and assessing the comparability of our measurement devices across groups and measures. One of the most consistently difficult concerns in management research over the past three decades has been trying to reconcile measurement equivalence issues utilizing diverse samples. Given the emphasis on diversity in the human resources area and the internationalization of business and management, measurement equivalence is more of a general concern now than ever before. If we are not able to successfully address concerns about measurement equivalence, research examining differences between groups could be highly misleading and/or erroneous. Consequently, we hope that the thoughtful contributions of the scholars in this volume will help future scholars to better address measurement equivalence concerns.
Several decades of psychometric research have led to the development of sophisticated models for multidimensional test data, and in recent years, multidimensional item response theory (MIRT) has become a burgeoning topic in psychological and educational measurement. Considered a cutting-edge statistical technique, the methodology underlying MIRT can be complex, and therefore doesn’t receive much attention in introductory IRT courses. However author Wes Bonifay shows how MIRT can be understood and applied by anyone with a firm grounding in unidimensional IRT modeling. His volume includes practical examples and illustrations, along with numerous figures and diagrams. Multidimensional Item Response Theory includes snippets of R code interspersed throughout the text (with the complete R code included on an accompanying website) to guide readers in exploring MIRT models, estimating the model parameters, generating plots, and implementing the various procedures and applications discussed throughout the book.
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.
Over the past thirty years, student assessment has become an increasingly important component of public education. A variety of methodologies in testing have been developed to obtain and interpret the wealth of assessment outcomes. As assessment goals are getting increasingly multifaceted, new testing methodologies are called for to provide more accessible and reliable information on more complex constructs or processes, such as students' critical thinking and problem-solving skills. Testing methodologies are needed to extract information from assessments on such complicated skills, in order to advise teachers about certain areas of students that need intervention. It is even a bigger challenge, and a vital mission of today’s large-scale assessments, to gain such information from testing data in an efficient manner. For example PARCC and Smarter Balanced Assessments consortia are both striving to offer formative assessments through individualized, tailored testing. The book provides state-of-the-art coverage on new methodologies to support tradit ional summative assessment, and more importantly, for emerging formative assessments.
The volume presents a broad spectrum of papers which illustrates a range of current research related to the theory, methods and applications of health related quality of life (HRQoL) as well as the interdisciplinary nature of this work.
Item-response theory (IRT) represents a key advance in measurement theory. Yet, it is largely absent from curricula, textbooks and popular statistical software, and often introduced through a subset of models. This Element, intended for creativity and innovation researchers, researchers-in-training, and anyone interested in how individual creativity might be measured, aims to provide 1) an overview of classical test theory (CTT) and its shortcomings in creativity measurement situations (e.g., fluency scores, consensual assessment technique, etc.); 2) an introduction to IRT and its core concepts, using a broad view of IRT that notably sees CTT models as particular cases of IRT; 3) a practical strategic approach to IRT modeling; 4) example applications of this strategy from creativity research and the associated advantages; and 5) ideas for future work that could advance how IRT could better benefit creativity research, as well as connections with other popular frameworks.