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Elements of Adaptive Testing / SpringerLink (Online service) ; van der Linden, Wim J ; Glas, Cees A.W (2010)
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Título : Elements of Adaptive Testing Tipo de documento: documento electrónico Autores: SpringerLink (Online service) ; van der Linden, Wim J ; Glas, Cees A.W Editorial: New York, NY : Springer New York Fecha de publicación: 2010 Colección: Statistics for Social and Behavioral Sciences, ISSN 2199-7357 Número de páginas: XIV, 438 p Il.: online resource ISBN/ISSN/DL: 978-0-387-85461-8 Idioma : Inglés (eng) Palabras clave: Statistics Assessment Psychometrics for Social Science, Behavorial Education, Public Policy, and Law Assessment, Testing Evaluation Clasificación: 51 Matemáticas Resumen: The arrival of the computer in educational and psychological testing has led to the current popularity of adaptive testing---a testing format in which the computer uses statistical information about the test items to automatically adapt their selection to a real-time update of the test taker’s ability estimate. This book covers such key features of adaptive testing as item selection and ability estimation, adaptive testing with multidimensional abilities, sequencing adaptive test batteries, multistage adaptive testing, item-pool design and maintenance, estimation of item and item-family parameters, item and person fit, as well as adaptive mastery and classification testing. It also shows how these features are used in the daily operations of several large-scale adaptive testing programs. Wim J. van der Linden is Chief Research Scientist at CTB/McGraw-Hill, Monterey, CA. His specialization is psychometric theory and methods, and he has been an active researcher of adaptive testing throughout his career. For Springer, he wrote Linear Models for Optimal Test Design (2005) and co-edited Handbook of Modern Item ResponseTheory (1997). He is a past president of the Psychometric Society and recipient of lifetime achievement awards from the National Council for Measurement in Education (NCME) and the Association of Test Publishers (ATP). Cees A. W. Glas is Professor of Social Science Research Methodology, University of Twente, the Netherlands. His specialization is psychometric theory and methods, with an emphasis on item response theory, adaptive testing, model fit analysis, and missing data. Professor Glas is a co-author of Educational Evaluation, Assessment, and Monitoring (Swets & Zetlinger, 2003). Currently, he is a member of the Editorial Board of Psychometrika and serves as a technical consultant to the OECD programs for international student assessment (PISA) and the assessment of adult competencies (PIAAC) Nota de contenido: ITEM SELECTION AND ABILITY ESTIMATION -- Item Selection and Ability Estimation in Adaptive Testing -- Constrained Adaptive Testing with Shadow Tests -- Principles of Multidimensional Adaptive Testing -- Multidimensional Adaptive Testing with Kullback#x2013;Leibler Information Item Selection -- Sequencing an Adaptive Test Battery -- APPLICATIONS IN LARGE-SCALE TESTING PROGRAMS -- Adaptive Tests for Measuring Anxiety and Depression -- MATHCAT: A Flexible Testing System in Mathematics Education for Adults -- Implementing the Graduate Management Admission Test Computerized Adaptive Test -- Designing and Implementing a Multistage Adaptive Test: The Uniform CPA Exam -- A Japanese Adaptive Test of English as a Foreign Language: Developmental and Operational Aspects -- ITEM POOL DEVELOPMENT AND MAINTENANCE -- Innovative Items for Computerized Testing -- Designing Item Pools for Adaptive Testing -- Assembling an Inventory of Multistage Adaptive Testing Systems -- ITEM CALIBRATION AND MODEL FIT -- Item Parameter Estimation and Item Fit Analysis -- Estimation of the Parameters in an Item-Cloning Model for Adaptive Testing -- Detecting Person Misfit in Adaptive Testing -- The Investigation of Differential Item Functioning in Adaptive Tests -- MULTISTAGE AND MASTERY TESTING -- Multistage Testing: Issues, Designs, and Research -- Three-Category Adaptive Classification Testing -- Testlet-Based Adaptive Mastery Testing -- Adaptive Mastery Testing Using a Multidimensional IRT Model En línea: http://dx.doi.org/10.1007/978-0-387-85461-8 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33513 Elements of Adaptive Testing [documento electrónico] / SpringerLink (Online service) ; van der Linden, Wim J ; Glas, Cees A.W . - New York, NY : Springer New York, 2010 . - XIV, 438 p : online resource. - (Statistics for Social and Behavioral Sciences, ISSN 2199-7357) .
ISBN : 978-0-387-85461-8
Idioma : Inglés (eng)
Palabras clave: Statistics Assessment Psychometrics for Social Science, Behavorial Education, Public Policy, and Law Assessment, Testing Evaluation Clasificación: 51 Matemáticas Resumen: The arrival of the computer in educational and psychological testing has led to the current popularity of adaptive testing---a testing format in which the computer uses statistical information about the test items to automatically adapt their selection to a real-time update of the test taker’s ability estimate. This book covers such key features of adaptive testing as item selection and ability estimation, adaptive testing with multidimensional abilities, sequencing adaptive test batteries, multistage adaptive testing, item-pool design and maintenance, estimation of item and item-family parameters, item and person fit, as well as adaptive mastery and classification testing. It also shows how these features are used in the daily operations of several large-scale adaptive testing programs. Wim J. van der Linden is Chief Research Scientist at CTB/McGraw-Hill, Monterey, CA. His specialization is psychometric theory and methods, and he has been an active researcher of adaptive testing throughout his career. For Springer, he wrote Linear Models for Optimal Test Design (2005) and co-edited Handbook of Modern Item ResponseTheory (1997). He is a past president of the Psychometric Society and recipient of lifetime achievement awards from the National Council for Measurement in Education (NCME) and the Association of Test Publishers (ATP). Cees A. W. Glas is Professor of Social Science Research Methodology, University of Twente, the Netherlands. His specialization is psychometric theory and methods, with an emphasis on item response theory, adaptive testing, model fit analysis, and missing data. Professor Glas is a co-author of Educational Evaluation, Assessment, and Monitoring (Swets & Zetlinger, 2003). Currently, he is a member of the Editorial Board of Psychometrika and serves as a technical consultant to the OECD programs for international student assessment (PISA) and the assessment of adult competencies (PIAAC) Nota de contenido: ITEM SELECTION AND ABILITY ESTIMATION -- Item Selection and Ability Estimation in Adaptive Testing -- Constrained Adaptive Testing with Shadow Tests -- Principles of Multidimensional Adaptive Testing -- Multidimensional Adaptive Testing with Kullback#x2013;Leibler Information Item Selection -- Sequencing an Adaptive Test Battery -- APPLICATIONS IN LARGE-SCALE TESTING PROGRAMS -- Adaptive Tests for Measuring Anxiety and Depression -- MATHCAT: A Flexible Testing System in Mathematics Education for Adults -- Implementing the Graduate Management Admission Test Computerized Adaptive Test -- Designing and Implementing a Multistage Adaptive Test: The Uniform CPA Exam -- A Japanese Adaptive Test of English as a Foreign Language: Developmental and Operational Aspects -- ITEM POOL DEVELOPMENT AND MAINTENANCE -- Innovative Items for Computerized Testing -- Designing Item Pools for Adaptive Testing -- Assembling an Inventory of Multistage Adaptive Testing Systems -- ITEM CALIBRATION AND MODEL FIT -- Item Parameter Estimation and Item Fit Analysis -- Estimation of the Parameters in an Item-Cloning Model for Adaptive Testing -- Detecting Person Misfit in Adaptive Testing -- The Investigation of Differential Item Functioning in Adaptive Tests -- MULTISTAGE AND MASTERY TESTING -- Multistage Testing: Issues, Designs, and Research -- Three-Category Adaptive Classification Testing -- Testlet-Based Adaptive Mastery Testing -- Adaptive Mastery Testing Using a Multidimensional IRT Model En línea: http://dx.doi.org/10.1007/978-0-387-85461-8 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33513 Ejemplares
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Título : Looking Back : Proceedings of a Conference in Honor of Paul W. Holland Tipo de documento: documento electrónico Autores: SpringerLink (Online service) ; Dorans, Neil J ; Sinharay, Sandip Editorial: New York, NY : Springer New York Fecha de publicación: 2011 Otro editor: Imprint: Springer Colección: Lecture Notes in Statistics, ISSN 0930-0325 num. 202 Número de páginas: XVIII, 283 p. 37 illus Il.: online resource ISBN/ISSN/DL: 978-1-4419-9389-2 Idioma : Inglés (eng) Palabras clave: Statistics Mathematics Assessment Social sciences Psychometrics for Science, Behavorial Education, Public Policy, and Law Assessment, Testing Evaluation Methodology of the Sciences Mathematics, general Clasificación: 51 Matemáticas Resumen: In 2006, Paul W. Holland retired from Educational Testing Service (ETS) after a career spanning five decades. In 2008, ETS sponsored a conference, Looking Back, honoring his contributions to applied and theoretical psychometrics and statistics. Looking Back attracted a large audience that came to pay homage to Paul Holland and to hear presentations by colleagues who worked with him in special ways over those 40+ years. This book contains papers based on these presentations, as well as vignettes provided by Paul Holland before each section. The papers in this book attest to how Paul Holland's pioneering ideas influenced and continue to influence several fields such as social networks, causal inference, item response theory, equating, and DIF. He applied statistical thinking to a broad range of ETS activities in test development, statistical analysis, test security, and operations. The original papers contained in this book provide historical context for Paul Holland’s work alongside commentary on some of his major contributions by noteworthy statisticians working today Nota de contenido: The Contributions of Paul Holland -- Algebraic Statistics for p1 Random Graph Models -- Mr. Holland's Networks: A Brief Review of the Importance of Statistical Studies of Local Subgraphs or One Small Tune in a Large Opus -- Some of My Favorite Things About Working at ETS -- Bayesian Analysis of a Two-Group Randomized Encouragement Design -- The Role of Nonparametric Analysis in Assessment Modeling: Then and Now -- What Aspects of the Design of an Observational Study Affect Its Sensitivity to Bias From Covariates That Were Not Observed? -- The Origins of Procedures for Using Differential Item Functioning Statistics at Educational Testing Service -- Why I Left ETS and Returned -- Cause or Effect? Validating the Use of Tests for High-Stakes Inferences in Education -- Propensity Score Matching to Extract Latent Experiments From Nonexperimental Data: A Case Study -- Returning to ETS from Berkeley -- Loglinear Models as Smooth Operators: Holland's Statistical Applications and Their Practical Uses -- Chain Equipercentile Equating and Frequency Estimation Equipercentile Equating: Comparisons Based on Real and Simulated Data -- An Observed-Score Equating Framework -- Great Colleagues Make a Great Institution -- An Exploratory Analysis of Charter Schools -- Holland's Advice for the Fourth Generation of Test Theory: Blood Tests Can Be Contests En línea: http://dx.doi.org/10.1007/978-1-4419-9389-2 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33183 Looking Back : Proceedings of a Conference in Honor of Paul W. Holland [documento electrónico] / SpringerLink (Online service) ; Dorans, Neil J ; Sinharay, Sandip . - New York, NY : Springer New York : Imprint: Springer, 2011 . - XVIII, 283 p. 37 illus : online resource. - (Lecture Notes in Statistics, ISSN 0930-0325; 202) .
ISBN : 978-1-4419-9389-2
Idioma : Inglés (eng)
Palabras clave: Statistics Mathematics Assessment Social sciences Psychometrics for Science, Behavorial Education, Public Policy, and Law Assessment, Testing Evaluation Methodology of the Sciences Mathematics, general Clasificación: 51 Matemáticas Resumen: In 2006, Paul W. Holland retired from Educational Testing Service (ETS) after a career spanning five decades. In 2008, ETS sponsored a conference, Looking Back, honoring his contributions to applied and theoretical psychometrics and statistics. Looking Back attracted a large audience that came to pay homage to Paul Holland and to hear presentations by colleagues who worked with him in special ways over those 40+ years. This book contains papers based on these presentations, as well as vignettes provided by Paul Holland before each section. The papers in this book attest to how Paul Holland's pioneering ideas influenced and continue to influence several fields such as social networks, causal inference, item response theory, equating, and DIF. He applied statistical thinking to a broad range of ETS activities in test development, statistical analysis, test security, and operations. The original papers contained in this book provide historical context for Paul Holland’s work alongside commentary on some of his major contributions by noteworthy statisticians working today Nota de contenido: The Contributions of Paul Holland -- Algebraic Statistics for p1 Random Graph Models -- Mr. Holland's Networks: A Brief Review of the Importance of Statistical Studies of Local Subgraphs or One Small Tune in a Large Opus -- Some of My Favorite Things About Working at ETS -- Bayesian Analysis of a Two-Group Randomized Encouragement Design -- The Role of Nonparametric Analysis in Assessment Modeling: Then and Now -- What Aspects of the Design of an Observational Study Affect Its Sensitivity to Bias From Covariates That Were Not Observed? -- The Origins of Procedures for Using Differential Item Functioning Statistics at Educational Testing Service -- Why I Left ETS and Returned -- Cause or Effect? Validating the Use of Tests for High-Stakes Inferences in Education -- Propensity Score Matching to Extract Latent Experiments From Nonexperimental Data: A Case Study -- Returning to ETS from Berkeley -- Loglinear Models as Smooth Operators: Holland's Statistical Applications and Their Practical Uses -- Chain Equipercentile Equating and Frequency Estimation Equipercentile Equating: Comparisons Based on Real and Simulated Data -- An Observed-Score Equating Framework -- Great Colleagues Make a Great Institution -- An Exploratory Analysis of Charter Schools -- Holland's Advice for the Fourth Generation of Test Theory: Blood Tests Can Be Contests En línea: http://dx.doi.org/10.1007/978-1-4419-9389-2 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33183 Ejemplares
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Título : Statistical Models for Test Equating, Scaling, and Linking Tipo de documento: documento electrónico Autores: SpringerLink (Online service) ; Davier, Alina A. von Editorial: New York, NY : Springer New York Fecha de publicación: 2011 Otro editor: Imprint: Springer Colección: Statistics for Social and Behavioral Sciences, ISSN 2199-7357 Número de páginas: XX, 368 p Il.: online resource ISBN/ISSN/DL: 978-0-387-98138-3 Idioma : Inglés (eng) Palabras clave: Education Assessment Statistics Psychometrics Assessment, Testing and Evaluation for Social Science, Behavorial Education, Public Policy, Law Clasificación: 51 Matemáticas Resumen: The goal of this book is to emphasize the formal statistical features of the practice of equating, linking, and scaling. The book encourages the view and discusses the quality of the equating results from the statistical perspective (new models, robustness, fit, testing hypotheses, statistical monitoring) as opposed to placing the focus on the policy and the implications, which although very important, represent a different side of the equating practice. The book contributes to establishing “equating” as a theoretical field, a view that has not been offered often before. The tradition in the practice of equating has been to present the knowledge and skills needed as a craft, which implies that only with years of experience under the guidance of a knowledgeable practitioner could one acquire the required skills. This book challenges this view by indicating how a good equating framework, a sound understanding of the assumptions that underlie the psychometric models, and the use of statistical tests and statistical process control tools can help the practitioner navigate the difficult decisions in choosing the final equating function. This book provides a valuable reference for several groups: (a) statisticians and psychometricians interested in the theory behind equating methods, in the use of model-based statistical methods for data smoothing, and in the evaluation of the equating results in applied work; (b) practitioners who need to equate tests, including those with these responsibilities in testing companies, state testing agencies, and school districts; and (c) instructors in psychometric, measurement, and psychology programs. Dr. Alina A. von Davier is a Strategic Advisor and a Director of Special Projects in Research and Development at Educational Testing Service (ETS). During her tenure at ETS, she has led an ETS Research Initiative called “Equating and Applied Psychometrics” and has directed the Global Psychometric Services Center. The center supports the psychometric work for all ETS international programs, including TOEFL iBT and TOEIC. She is a co-author of a book on the kernel method of test equating, an author of a book on hypotheses testing in regression models, and a guest co-editor for a special issue on population invariance of linking functions for the journal Applied Psychological Measurement Nota de contenido: Overview -- A Statistical Perspective on Equating Test Scores (Alina A. von Davier) -- Part I: Research Questions and Data Collection Designs -- Equating Test Scores: Toward Best Practices Neil J. Dorans, Tim P. Moses, and Daniel R. Eignor) -- Scoring and Scaling Educational Tests Michael J. Kolen, Ye Tong, and Robert L. Brennan) -- Statistical Models for Vertical Linking James E. Carlson) -- An Empirical Example of Change Analysis by Linking Longitudinal Item Response Data From Multiple Tests (John J. McArdle and Kevin J. Grimm) -- How to Average Equating Functions, If You Must (Paul W. Holland and William E. Strawderman) -- New Approaches to Equating With Small Samples (Samuel A. Livingston and Sooyeon Kim) -- Part II: Measurement and Equating Models -- Using Exponential Families for Equating (Shelby J. Haberman) -- An Alternative Continuization Method: The Continuized Log-Linear Method (Tianyou Wang) -- Equating Through Alternative Kernels (Yi-Hsuan Lee and Alina A. von Davier) -- A Bayesian Nonparametric Model for Test Equating (George Karabatsos and Stephen G. Walker) -- Generalized Equating Functions for NEAT Designs (Haiwen H. Chen, Samuel A. Livingston, and Paul W. Holland) -- Local Observed-Score Equating (Wim J. van der Linden) -- A General Model for IRT Scale Linking and Scale Transformations (Matthias von Davier and Alina A. von Davier) -- Linking With Nonparametric IRT Models (Xueli Xu, Jeff A. Douglas, and Young-Sun Lee) -- Part III: Evaluation -- Applications of Asymptotic Expansion in Item Response Theory Linking (Haruhiko Ogasawara) -- Evaluating the Missing Data Assumptions of the Chain and Poststratification Equating Methods (Sandip Sinharay, Paul W. Holland, and Alina A. von Davier) -- Robustness of IRT Observed-Score Equating (C. A. W. Glas and Anton A. Beguin) -- Hypothesis Testing of Equating Differences in the Kernel Equating Framework (Frank Rijmen, Yanxuan Qu, and Alina A. von Davier) -- Applying Time-Series Analysis to Detect Scale Drift (Deping Li, Shuhong Li, and Alina A. von Davier) En línea: http://dx.doi.org/10.1007/978-0-387-98138-3 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33085 Statistical Models for Test Equating, Scaling, and Linking [documento electrónico] / SpringerLink (Online service) ; Davier, Alina A. von . - New York, NY : Springer New York : Imprint: Springer, 2011 . - XX, 368 p : online resource. - (Statistics for Social and Behavioral Sciences, ISSN 2199-7357) .
ISBN : 978-0-387-98138-3
Idioma : Inglés (eng)
Palabras clave: Education Assessment Statistics Psychometrics Assessment, Testing and Evaluation for Social Science, Behavorial Education, Public Policy, Law Clasificación: 51 Matemáticas Resumen: The goal of this book is to emphasize the formal statistical features of the practice of equating, linking, and scaling. The book encourages the view and discusses the quality of the equating results from the statistical perspective (new models, robustness, fit, testing hypotheses, statistical monitoring) as opposed to placing the focus on the policy and the implications, which although very important, represent a different side of the equating practice. The book contributes to establishing “equating” as a theoretical field, a view that has not been offered often before. The tradition in the practice of equating has been to present the knowledge and skills needed as a craft, which implies that only with years of experience under the guidance of a knowledgeable practitioner could one acquire the required skills. This book challenges this view by indicating how a good equating framework, a sound understanding of the assumptions that underlie the psychometric models, and the use of statistical tests and statistical process control tools can help the practitioner navigate the difficult decisions in choosing the final equating function. This book provides a valuable reference for several groups: (a) statisticians and psychometricians interested in the theory behind equating methods, in the use of model-based statistical methods for data smoothing, and in the evaluation of the equating results in applied work; (b) practitioners who need to equate tests, including those with these responsibilities in testing companies, state testing agencies, and school districts; and (c) instructors in psychometric, measurement, and psychology programs. Dr. Alina A. von Davier is a Strategic Advisor and a Director of Special Projects in Research and Development at Educational Testing Service (ETS). During her tenure at ETS, she has led an ETS Research Initiative called “Equating and Applied Psychometrics” and has directed the Global Psychometric Services Center. The center supports the psychometric work for all ETS international programs, including TOEFL iBT and TOEIC. She is a co-author of a book on the kernel method of test equating, an author of a book on hypotheses testing in regression models, and a guest co-editor for a special issue on population invariance of linking functions for the journal Applied Psychological Measurement Nota de contenido: Overview -- A Statistical Perspective on Equating Test Scores (Alina A. von Davier) -- Part I: Research Questions and Data Collection Designs -- Equating Test Scores: Toward Best Practices Neil J. Dorans, Tim P. Moses, and Daniel R. Eignor) -- Scoring and Scaling Educational Tests Michael J. Kolen, Ye Tong, and Robert L. Brennan) -- Statistical Models for Vertical Linking James E. Carlson) -- An Empirical Example of Change Analysis by Linking Longitudinal Item Response Data From Multiple Tests (John J. McArdle and Kevin J. Grimm) -- How to Average Equating Functions, If You Must (Paul W. Holland and William E. Strawderman) -- New Approaches to Equating With Small Samples (Samuel A. Livingston and Sooyeon Kim) -- Part II: Measurement and Equating Models -- Using Exponential Families for Equating (Shelby J. Haberman) -- An Alternative Continuization Method: The Continuized Log-Linear Method (Tianyou Wang) -- Equating Through Alternative Kernels (Yi-Hsuan Lee and Alina A. von Davier) -- A Bayesian Nonparametric Model for Test Equating (George Karabatsos and Stephen G. Walker) -- Generalized Equating Functions for NEAT Designs (Haiwen H. Chen, Samuel A. Livingston, and Paul W. Holland) -- Local Observed-Score Equating (Wim J. van der Linden) -- A General Model for IRT Scale Linking and Scale Transformations (Matthias von Davier and Alina A. von Davier) -- Linking With Nonparametric IRT Models (Xueli Xu, Jeff A. Douglas, and Young-Sun Lee) -- Part III: Evaluation -- Applications of Asymptotic Expansion in Item Response Theory Linking (Haruhiko Ogasawara) -- Evaluating the Missing Data Assumptions of the Chain and Poststratification Equating Methods (Sandip Sinharay, Paul W. Holland, and Alina A. von Davier) -- Robustness of IRT Observed-Score Equating (C. A. W. Glas and Anton A. Beguin) -- Hypothesis Testing of Equating Differences in the Kernel Equating Framework (Frank Rijmen, Yanxuan Qu, and Alina A. von Davier) -- Applying Time-Series Analysis to Detect Scale Drift (Deping Li, Shuhong Li, and Alina A. von Davier) En línea: http://dx.doi.org/10.1007/978-0-387-98138-3 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33085 Ejemplares
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Título : Bayesian Item Response Modeling : Theory and Applications Tipo de documento: documento electrónico Autores: Fox, Jean-Paul ; SpringerLink (Online service) Editorial: New York, NY : Springer New York Fecha de publicación: 2010 Colección: Statistics for Social and Behavioral Sciences, ISSN 2199-7357 Número de páginas: XIV, 313 p Il.: online resource ISBN/ISSN/DL: 978-1-4419-0742-4 Idioma : Inglés (eng) Palabras clave: Social sciences Marketing Probabilities Assessment Statistics Psychometrics Sciences Methodology of the Probability Theory and Stochastic Processes for Science, Behavorial Education, Public Policy, Law Assessment, Testing Evaluation Clasificación: 51 Matemáticas Resumen: This book presents a thorough treatment and unified coverage of Bayesian item response modeling with applications in a variety of disciplines, including education, medicine, psychology, and sociology. Breakthroughs in computing technology have made the Bayesian approach particularly useful for many response modeling problems. Free from computational constraints, realistic and state-of-the-art latent variable response models are considered for complex assessment and survey data to solve real-world problems. The Bayesian framework described provides a unified approach for modeling and inference, dealing with (nondata) prior information and information across multiple data sources. The book discusses methods for analyzing item response data and the complex relationships commonly associated with human response behavior and features • Self-contained introduction to Bayesian item response modeling and a coverage of extending standard models to handle complex assessment data • A thorough overview of Bayesian estimation and testing methods for item response models, where MCMC methods are emphasized • Numerous examples that cover a wide range of application areas, including education, medicine, psychology, and sociology • Datasets and software (S+, R, and WinBUGS code) of the models and methods presented in the book are available on www.jean-paulfox.com Bayesian Item Response Modeling is an excellent book for research professionals, including applied statisticians, psychometricians, and social scientists who analyze item response data from a Bayesian perspective. It is a guide to the growing area of Bayesian response modeling for researchers and graduate students, and will also serve them as a good reference. Jean-Paul Fox is Associate Professor of Measurement and Data Analysis, University of Twente, The Netherlands. His main research activities are in several areas of Bayesian response modeling. Dr. Fox has published numerous articles in the areas of Bayesian item response analysis, statistical methods for analyzing multivariate categorical response data, and nonlinear mixed effects models Nota de contenido: to Bayesian Response Modeling -- Bayesian Hierarchical Response Modeling -- Basic Elements of Bayesian Statistics -- Estimation of Bayesian Item Response Models -- Assessment of Bayesian Item Response Models -- Multilevel Item Response Theory Models -- Random Item Effects Models -- Response Time Item Response Models -- Randomized Item Response Models En línea: http://dx.doi.org/10.1007/978-1-4419-0742-4 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33580 Bayesian Item Response Modeling : Theory and Applications [documento electrónico] / Fox, Jean-Paul ; SpringerLink (Online service) . - New York, NY : Springer New York, 2010 . - XIV, 313 p : online resource. - (Statistics for Social and Behavioral Sciences, ISSN 2199-7357) .
ISBN : 978-1-4419-0742-4
Idioma : Inglés (eng)
Palabras clave: Social sciences Marketing Probabilities Assessment Statistics Psychometrics Sciences Methodology of the Probability Theory and Stochastic Processes for Science, Behavorial Education, Public Policy, Law Assessment, Testing Evaluation Clasificación: 51 Matemáticas Resumen: This book presents a thorough treatment and unified coverage of Bayesian item response modeling with applications in a variety of disciplines, including education, medicine, psychology, and sociology. Breakthroughs in computing technology have made the Bayesian approach particularly useful for many response modeling problems. Free from computational constraints, realistic and state-of-the-art latent variable response models are considered for complex assessment and survey data to solve real-world problems. The Bayesian framework described provides a unified approach for modeling and inference, dealing with (nondata) prior information and information across multiple data sources. The book discusses methods for analyzing item response data and the complex relationships commonly associated with human response behavior and features • Self-contained introduction to Bayesian item response modeling and a coverage of extending standard models to handle complex assessment data • A thorough overview of Bayesian estimation and testing methods for item response models, where MCMC methods are emphasized • Numerous examples that cover a wide range of application areas, including education, medicine, psychology, and sociology • Datasets and software (S+, R, and WinBUGS code) of the models and methods presented in the book are available on www.jean-paulfox.com Bayesian Item Response Modeling is an excellent book for research professionals, including applied statisticians, psychometricians, and social scientists who analyze item response data from a Bayesian perspective. It is a guide to the growing area of Bayesian response modeling for researchers and graduate students, and will also serve them as a good reference. Jean-Paul Fox is Associate Professor of Measurement and Data Analysis, University of Twente, The Netherlands. His main research activities are in several areas of Bayesian response modeling. Dr. Fox has published numerous articles in the areas of Bayesian item response analysis, statistical methods for analyzing multivariate categorical response data, and nonlinear mixed effects models Nota de contenido: to Bayesian Response Modeling -- Bayesian Hierarchical Response Modeling -- Basic Elements of Bayesian Statistics -- Estimation of Bayesian Item Response Models -- Assessment of Bayesian Item Response Models -- Multilevel Item Response Theory Models -- Random Item Effects Models -- Response Time Item Response Models -- Randomized Item Response Models En línea: http://dx.doi.org/10.1007/978-1-4419-0742-4 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33580 Ejemplares
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Título : Linear Models for Optimal Test Design Tipo de documento: documento electrónico Autores: Linden, Wim J. van der ; SpringerLink (Online service) Editorial: New York, NY : Springer New York Fecha de publicación: 2005 Colección: Statistics for Social and Behavioral Sciences, ISSN 2199-7357 Número de páginas: XXIV, 408 p. 44 illus Il.: online resource ISBN/ISSN/DL: 978-0-387-29054-6 Idioma : Inglés (eng) Palabras clave: Statistics Assessment Psychometrics for Social Science, Behavorial Education, Public Policy, and Law Assessment, Testing Evaluation Clasificación: 51 Matemáticas Resumen: This book begins with a reflection on the history of test design--the core activity of all educational and psychological testing. It then presents a standard language for modeling test design problems as instances of multi-objective constrained optimization. The main portion of the book discusses test design models for a large variety of problems from the daily practice of testing, and illustrates their use with the help of numerous empirical examples. The presentation includes models for the assembly of tests to an absolute or relative target for their information functions, classical test assembly, test equating problems, item matching, test splitting, simultaneous assembly of multiple tests, tests with item sets, multidimensional tests, and adaptive test assembly. Two separate chapters are devoted to the questions of how to design item banks for optimal support of programs with fixed and adaptive tests. Linear Models for Optimal Test Design, which does not require any specific mathematical background, has been written to be a helpful resource on the desk of any test specialist. Wim J. van der Linden is Professor of Measurement and Data Analysis, University of Twente, The Netherlands. His specialization is psychometric theory and methods, and he has been an active researcher of item response theory throughout his career. His current research is on test design, adaptive testing, test equating, and response-time modeling. Professor van der Linden is a past president of the Psychometric Society and a recipient of the NCME lifetime achievement award for his work on educational measurement Nota de contenido: Brief History of Test Theory and Design -- Formulating Test Specifications -- Modeling Test-Assembly Problems -- Solving Test-Assembly Problems -- Models for Assembling Single Tests -- Models for Assembling Multiple Tests -- Models for Assembling Tests with Item Sets -- Models for Assembling Tests Measuring Multiple Abilities -- Models for Adaptive Test Assembly -- Designing Item Pools for Programs with Fixed Tests -- Designing Item Pools for Programs with Adaptive Tests -- Epilogue En línea: http://dx.doi.org/10.1007/0-387-29054-0 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=35162 Linear Models for Optimal Test Design [documento electrónico] / Linden, Wim J. van der ; SpringerLink (Online service) . - New York, NY : Springer New York, 2005 . - XXIV, 408 p. 44 illus : online resource. - (Statistics for Social and Behavioral Sciences, ISSN 2199-7357) .
ISBN : 978-0-387-29054-6
Idioma : Inglés (eng)
Palabras clave: Statistics Assessment Psychometrics for Social Science, Behavorial Education, Public Policy, and Law Assessment, Testing Evaluation Clasificación: 51 Matemáticas Resumen: This book begins with a reflection on the history of test design--the core activity of all educational and psychological testing. It then presents a standard language for modeling test design problems as instances of multi-objective constrained optimization. The main portion of the book discusses test design models for a large variety of problems from the daily practice of testing, and illustrates their use with the help of numerous empirical examples. The presentation includes models for the assembly of tests to an absolute or relative target for their information functions, classical test assembly, test equating problems, item matching, test splitting, simultaneous assembly of multiple tests, tests with item sets, multidimensional tests, and adaptive test assembly. Two separate chapters are devoted to the questions of how to design item banks for optimal support of programs with fixed and adaptive tests. Linear Models for Optimal Test Design, which does not require any specific mathematical background, has been written to be a helpful resource on the desk of any test specialist. Wim J. van der Linden is Professor of Measurement and Data Analysis, University of Twente, The Netherlands. His specialization is psychometric theory and methods, and he has been an active researcher of item response theory throughout his career. His current research is on test design, adaptive testing, test equating, and response-time modeling. Professor van der Linden is a past president of the Psychometric Society and a recipient of the NCME lifetime achievement award for his work on educational measurement Nota de contenido: Brief History of Test Theory and Design -- Formulating Test Specifications -- Modeling Test-Assembly Problems -- Solving Test-Assembly Problems -- Models for Assembling Single Tests -- Models for Assembling Multiple Tests -- Models for Assembling Tests with Item Sets -- Models for Assembling Tests Measuring Multiple Abilities -- Models for Adaptive Test Assembly -- Designing Item Pools for Programs with Fixed Tests -- Designing Item Pools for Programs with Adaptive Tests -- Epilogue En línea: http://dx.doi.org/10.1007/0-387-29054-0 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=35162 Ejemplares
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