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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 this book, the authors provide a cogent review of statistical and interpretive procedures that, in combination, can be used to reduce the likelihood that tests contain items that favor members of one gender, age, racial, or ethnic group over equally able members of another group, for reasons that are unrelated to the objectives and purposes of measurement. Such test items are said to be biased against the equally able members of the group that is not favored. The methods described and illustrated in this book have the potential to reducing the incidence of tests that are, in their construction, biased against members of one or more groups. These methods have the potential of controlling an important source of invalidity when test results are interpreted.
Test fairness is a moral imperative for both the makers and the users of tests. This book focuses on methods for detecting test items that function differently for different groups of examinees and on using this information to improve tests. Of interest to all testing and measurement specialists, it examines modern techniques used routinely to insure test fairness. Three of these relevant to the book's contents are: * detailed reviews of test items by subject matter experts and members of the major subgroups in society (gender, ethnic, and linguistic) that will be represented in the examinee population * comparisons of the predictive validity of the test done separately for each one of the major subgroups of examinees * extensive statistical analyses of the relative performance of major subgroups of examinees on individual test items.
Using a meaning-based approach that emphasizes the “why” over the “how to,” Psychometrics: An Introduction provides thorough coverage of fundamental issues in psychological measurement. Author R. Michael Furr discusses traditional psychometric perspectives and issues including reliability, validity, dimensionality, test bias, and response bias as well as advanced procedures and perspectives including item response theory and generalizability theory. The substantially updated Third Edition includes broader and more in-depth coverage with new references, a glossary summarizing over 200 key terms, and expanded suggested readings consisting of highly relevant papers to enhance the book’s overall accessibility, scope, and usability.
This volume addresses an urgent need across multiple disciplines to broaden our understanding and use of response processes evidence of test validity. It builds on the themes and findings of the volume Validity and Validation in Social, Behavioral, and Health Sciences (Zumbo & Chan, 2014), with a focus on measurement validity evidence based on response processes. Approximately 1000 studies are published each year examining the validity of inferences made from tests and measures in the social, behavioural, and health sciences. The widely accepted Standards for Educational and Psychological Testing (1999, 2014) present five sources of evidence for validity: content-related, response processes, internal structure, relationships with other variables, and consequences of testing. Many studies focus on internal structure and relationships with other variables sources of evidence, which have a long history in validation research, known methodologies, and numerous exemplars in the literature. Far less is understood by test users and researchers conducting validation work about how to think about and apply new and emerging sources of validity evidence. This groundbreaking volume is the first to present conceptual models of response processes, methodological issues that arise in gathering response processes evidence, as well as applications and exemplars for providing response processes evidence in validation work.
Sponsored by Division 15 of APA, the second edition of this groundbreaking book has been expanded to 41 chapters that provide unparalleled coverage of this far-ranging field. Internationally recognized scholars contribute up-to-date reviews and critical syntheses of the following areas: foundations and the future of educational psychology, learners’ development, individual differences, cognition, motivation, content area teaching, socio-cultural perspectives on teaching and learning, teachers and teaching, instructional design, teacher assessment, and modern perspectives on research methodologies, data, and data analysis. New chapters cover topics such as adult development, self-regulation, changes in knowledge and beliefs, and writing. Expanded treatment has been given to cognition, motivation, and new methodologies for gathering and analyzing data. The Handbook of Educational Psychology, Second Edition provides an indispensable reference volume for scholars, teacher educators, in-service practitioners, policy makers and the academic libraries serving these audiences. It is also appropriate for graduate level courses devoted to the study of educational psychology.
Includes established theories and cutting-edge developments. Presents the work of an international group of experts. Presents the nature, origin, implications, an future course of major unresolved issues in the area.
Educational Measurement has been the bible in its field since the first edition was published by ACE in 1951. The importance of this fourth edition of Educational Measurement is to extensively update and extend the topics treated in the previous three editions. As such, the fourth edition documents progress in the field and provides critical guidance to the efforts of new generations of researchers and practitioners. Edited by Robert Brennan and jointly sponsored by the American Council on Education (ACE) and the National Council on Measurement in Education, the fourth edition provides in-depth treatments of critical measurement topics, and the chapter authors are acknowledged experts in their respective fields. Educational measurement researchers and practitioners will find this text essential, and those interested in statistics, psychology, business, and economics should also find this work to be of very strong interest. Topics covered are divided into three subject areas: theory and general principles; construction, administration, and scoring; and applications. The first part of the book covers the topics of validation, reliability, item response theory, scaling and norming, linking and equating, test fairness, and cognitive psychology. Part two includes chapters on test development, test administration, performance assessment, setting performance standards, and technology in testing. The final section includes chapters on second language testing, testing for accountability in K-12 schools, standardized assessment of individual achievement in K-12 schools, higher education admissions testing, monitoring educational progress, licensure and certification testing, and legal and ethical issues.
`I often... wonder to myself whether the field needs another book, handbook, or encyclopedia on this topic. In this case I think that the answer is truly yes. The handbook is well focused on important issues in the field, and the chapters are written by recognized authorities in their fields. The book should appeal to anyone who wants an understanding of important topics that frequently go uncovered in graduate education in psychology′ - David C Howell, Professor Emeritus, University of Vermont Quantitative psychology is arguably one of the oldest disciplines within the field of psychology and nearly all psychologists are exposed to quantitative psychology in some form. While textbooks in statistics, research methods and psychological measurement exist, none offer a unified treatment of quantitative psychology. The SAGE Handbook of Quantitative Methods in Psychology does just that. Each chapter covers a methodological topic with equal attention paid to established theory and the challenges facing methodologists as they address new research questions using that particular methodology. The reader will come away from each chapter with a greater understanding of the methodology being addressed as well as an understanding of the directions for future developments within that methodological area. Drawing on a global scholarship, the Handbook is divided into seven parts: Part One: Design and Inference: addresses issues in the inference of causal relations from experimental and non-experimental research, along with the design of true experiments and quasi-experiments, and the problem of missing data due to various influences such as attrition or non-compliance. Part Two: Measurement Theory: begins with a chapter on classical test theory, followed by the common factor analysis model as a model for psychological measurement. The models for continuous latent variables in item-response theory are covered next, followed by a chapter on discrete latent variable models as represented in latent class analysis. Part Three: Scaling Methods: covers metric and non-metric scaling methods as developed in multidimensional scaling, followed by consideration of the scaling of discrete measures as found in dual scaling and correspondence analysis. Models for preference data such as those found in random utility theory are covered next. Part Four: Data Analysis: includes chapters on regression models, categorical data analysis, multilevel or hierarchical models, resampling methods, robust data analysis, meta-analysis, Bayesian data analysis, and cluster analysis. Part Five: Structural Equation Models: addresses topics in general structural equation modeling, nonlinear structural equation models, mixture models, and multilevel structural equation models. Part Six: Longitudinal Models: covers the analysis of longitudinal data via mixed modeling, time series analysis and event history analysis. Part Seven: Specialized Models: covers specific topics including the analysis of neuro-imaging data and functional data-analysis.