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Título : Multivariate and Mixture Distribution Rasch Models : Extensions and Applications Tipo de documento: documento electrónico Autores: Matthias von Davier ; SpringerLink (Online service) ; Claus H. Carstensen Editorial: New York, NY : Springer New York Fecha de publicación: 2007 Otro editor: Imprint: Springer Colección: Statistics for Social and Behavioral Sciences, ISSN 2199-7357 Número de páginas: XIII, 398 p. 42 illus Il.: online resource ISBN/ISSN/DL: 978-0-387-49839-3 Idioma : Inglés (eng) Palabras clave: Statistics Medical research Education Quality of life Psychology Methodology Psychological measurement Psychometrics for Social Science, Behavorial Education, Public Policy, and Law general Life Research Methods/Evaluation Clasificación: 51 Matemáticas Resumen: This volume covers extensions of the Rasch model, one of the most researched and applied models in educational research and social science. This collection contains 22 chapters by some of the most recognized international experts in the field. They cover topics ranging from general model extensions to applications in fields as diverse as cognition, personality, organizational and sports psychology, and health sciences and education. The Rasch model is designed for categorical data, often collected as examinees' responses to multiple tasks such as cognitive items from psychological tests or from educational assessments. The Rasch model's elegant mathematical form is suitable for extensions that allow for greater flexibility in handling complex samples of examinees and collections of tasks from different domains. In these extensions, the Rasch model is enhanced by additional structural elements that either account for differences between diverse populations or for differences among observed variables. Research on extending well-known statistical tools like regression, mixture distribution, and hierarchical linear models has led to the adoption of Rasch model features to handle categorical observed variables. We maintain both perspectives in the volume and show how these merged models—Rasch models with a more complex item or population structure—are derived either from the Rasch model or from a structural model, how they are estimated, and where they are applied. Matthias von Davier is a Senior Research Scientist in the Research & Development Division at Educational Testing Service. He is the author of WINMIRA, a software package for estimating latent class models, mixture distribution Rasch models, and hybrid Rasch models. The software grew out of his work with colleagues at the Methodology Department of the Institute for Science Education (IPN) in Kiel, Germany. Von Davier's current research is concerned with extensions of Rasch models and more general Item Response Theory (IRT) models to multidimensional, diagnostic models and with mixture distribution models, with statistical computation and estimation, and with applications of psychometric models in national and international educational assessments. Claus H. Carstensen is a junior Professor in the Psychometrics and Methodology Department at the IPN, Carstensen's work is concerned with multidimensional extensions of the Rasch model and applications of these models in intelligence and expertise research and educational assessments. He and Juergen Rost, head of the IPN's Methodology Department at the time, developed MULTIRA, a software package for multidimensional Rasch models. Before his current position, Carstensen was a Research Officer at the Australian Council of Educational Research where his focus was large-scale data analysis using multidimensional extensions of the Rasch model Nota de contenido: Introduction: Extending the Rasch Model -- Introduction: Extending the Rasch Model -- Multivariate and Mixture Rasch Models -- Measurement Models as Narrative Structures -- Testing Generalized Rasch Models -- The Mixed-Coefficients Multinomial Logit Model: A Generalized Form of the Rasch Model -- Loglinear Multivariate and Mixture Rasch Models -- Mixture-Distribution and HYBRID Rasch Models -- Generalized Models—Specific Research Questions -- Application of the Saltus Model to Stagelike Data: Some Applications and Current Developments -- Determination of Diagnostic Cut-Points Using Stochastically Ordered Mixed Rasch Models -- A HYBRID Model for Test Speededness -- Multidimensional Three-Mode Rasch Models -- (Almost) Equivalence Between Conditional and Mixture Maximum Likelihood Estimates for Some Models of the Rasch Type -- Rasch Models for Longitudinal Data -- The Interaction Model -- Multilevel Rasch Models -- Applications of Multivariate and Mixed Rasch Models -- Mixed Rasch Models for Measurement in Cognitive Psychology -- Detecting Response Styles and Faking in Personality and Organizational Assessments by Mixed Rasch Models -- Application of Multivariate Rasch Models in International Large-Scale Educational Assessments -- Studying Development via Item Response Models: A Wide Range of Potential Uses -- A Comparison of the Rasch Model and Constrained Item Response Theory Models for Pertinent Psychological Test Data -- Latent-Response Rasch Models for Strategy Shifts in Problem-Solving Processes -- Validity and Objectivity in Health-Related Scales: Analysis by Graphical Loglinear Rasch Models -- Applications of Generalized Rasch Models in the Sport, Exercise, and the Motor Domains En línea: http://dx.doi.org/10.1007/978-0-387-49839-3 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=34498 Multivariate and Mixture Distribution Rasch Models : Extensions and Applications [documento electrónico] / Matthias von Davier ; SpringerLink (Online service) ; Claus H. Carstensen . - New York, NY : Springer New York : Imprint: Springer, 2007 . - XIII, 398 p. 42 illus : online resource. - (Statistics for Social and Behavioral Sciences, ISSN 2199-7357) .
ISBN : 978-0-387-49839-3
Idioma : Inglés (eng)
Palabras clave: Statistics Medical research Education Quality of life Psychology Methodology Psychological measurement Psychometrics for Social Science, Behavorial Education, Public Policy, and Law general Life Research Methods/Evaluation Clasificación: 51 Matemáticas Resumen: This volume covers extensions of the Rasch model, one of the most researched and applied models in educational research and social science. This collection contains 22 chapters by some of the most recognized international experts in the field. They cover topics ranging from general model extensions to applications in fields as diverse as cognition, personality, organizational and sports psychology, and health sciences and education. The Rasch model is designed for categorical data, often collected as examinees' responses to multiple tasks such as cognitive items from psychological tests or from educational assessments. The Rasch model's elegant mathematical form is suitable for extensions that allow for greater flexibility in handling complex samples of examinees and collections of tasks from different domains. In these extensions, the Rasch model is enhanced by additional structural elements that either account for differences between diverse populations or for differences among observed variables. Research on extending well-known statistical tools like regression, mixture distribution, and hierarchical linear models has led to the adoption of Rasch model features to handle categorical observed variables. We maintain both perspectives in the volume and show how these merged models—Rasch models with a more complex item or population structure—are derived either from the Rasch model or from a structural model, how they are estimated, and where they are applied. Matthias von Davier is a Senior Research Scientist in the Research & Development Division at Educational Testing Service. He is the author of WINMIRA, a software package for estimating latent class models, mixture distribution Rasch models, and hybrid Rasch models. The software grew out of his work with colleagues at the Methodology Department of the Institute for Science Education (IPN) in Kiel, Germany. Von Davier's current research is concerned with extensions of Rasch models and more general Item Response Theory (IRT) models to multidimensional, diagnostic models and with mixture distribution models, with statistical computation and estimation, and with applications of psychometric models in national and international educational assessments. Claus H. Carstensen is a junior Professor in the Psychometrics and Methodology Department at the IPN, Carstensen's work is concerned with multidimensional extensions of the Rasch model and applications of these models in intelligence and expertise research and educational assessments. He and Juergen Rost, head of the IPN's Methodology Department at the time, developed MULTIRA, a software package for multidimensional Rasch models. Before his current position, Carstensen was a Research Officer at the Australian Council of Educational Research where his focus was large-scale data analysis using multidimensional extensions of the Rasch model Nota de contenido: Introduction: Extending the Rasch Model -- Introduction: Extending the Rasch Model -- Multivariate and Mixture Rasch Models -- Measurement Models as Narrative Structures -- Testing Generalized Rasch Models -- The Mixed-Coefficients Multinomial Logit Model: A Generalized Form of the Rasch Model -- Loglinear Multivariate and Mixture Rasch Models -- Mixture-Distribution and HYBRID Rasch Models -- Generalized Models—Specific Research Questions -- Application of the Saltus Model to Stagelike Data: Some Applications and Current Developments -- Determination of Diagnostic Cut-Points Using Stochastically Ordered Mixed Rasch Models -- A HYBRID Model for Test Speededness -- Multidimensional Three-Mode Rasch Models -- (Almost) Equivalence Between Conditional and Mixture Maximum Likelihood Estimates for Some Models of the Rasch Type -- Rasch Models for Longitudinal Data -- The Interaction Model -- Multilevel Rasch Models -- Applications of Multivariate and Mixed Rasch Models -- Mixed Rasch Models for Measurement in Cognitive Psychology -- Detecting Response Styles and Faking in Personality and Organizational Assessments by Mixed Rasch Models -- Application of Multivariate Rasch Models in International Large-Scale Educational Assessments -- Studying Development via Item Response Models: A Wide Range of Potential Uses -- A Comparison of the Rasch Model and Constrained Item Response Theory Models for Pertinent Psychological Test Data -- Latent-Response Rasch Models for Strategy Shifts in Problem-Solving Processes -- Validity and Objectivity in Health-Related Scales: Analysis by Graphical Loglinear Rasch Models -- Applications of Generalized Rasch Models in the Sport, Exercise, and the Motor Domains En línea: http://dx.doi.org/10.1007/978-0-387-49839-3 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=34498 Ejemplares
Signatura Medio Ubicación Sub-localización Sección Estado ningún ejemplar Linking and Aligning Scores and Scales / SpringerLink (Online service) ; Neil J. Dorans ; Mary Pommerich ; Paul W. Holland (2007)
Título : Linking and Aligning Scores and Scales Tipo de documento: documento electrónico Autores: SpringerLink (Online service) ; Neil J. Dorans ; Mary Pommerich ; Paul W. Holland Editorial: New York, NY : Springer New York Fecha de publicación: 2007 Colección: Statistics for Social and Behavioral Sciences, ISSN 2199-7357 Número de páginas: XX, 396 p Il.: online resource ISBN/ISSN/DL: 978-0-387-49771-6 Idioma : Inglés (eng) Palabras clave: Statistics Assessment Psychology Methodology Psychological measurement Psychometrics for Social Science, Behavorial Education, Public Policy, and Law Assessment, Testing Evaluation Methods/Evaluation Clasificación: 51 Matemáticas Resumen: The comparability of measurements made in differing circumstances by different methods and investigators is a fundamental pre-condition for all of science. Successful applications of technology require comparable measurements. While the applications herefocus on educational tests, score linking issues are directly applicable to medicine and many branches of behavioral science. Since the 1980s, the fields of educational and psychological measurement have enhanced and widely applied techniques for producing linked scores that are comparable. The interpretation attached to a linkage depends on how the conditions of the linkage differ from the ideal. In this book, experts in statistics and psychometrics describe classes of linkages, the history of score linkings, data collection designs, and methods used to achieve sound score linkages. They describe and critically discuss applications to a variety of domains including equating of achievement exams, linkages between computer-delivered exams and paper-and-pencil exams, concordances between the current version of the SAT® and its predecessor, concordances between the ACT® and the SAT®, vertical linkages of exams that span grade levels, and linkages of scales from high-stakes state assessments to the scales of the National Assessment of Educational Progress (NAEP). Dr. Neil J. Dorans is a Distinguished Presidential Appointee at Educational Testing Service. During his 27 years at ETS, he has had primary responsibility for the statistical work associated with the AP®, PSAT/NMSQT®, and SAT® exams. He was the architect for the recentered SAT scales. He has guest edited special issues on score linking for Applied Measurement in Education, Applied Psychological Measurement, and the Journal of Educational Measurement. Dr. Mary Pommerich is a psychometrician in the Personnel Testing Division of the Defense Manpower Data Center, where she works with the ASVAB (Armed Services Vocational Aptitude Battery) testing program. She guest edited a special issue on concordance for Applied Psychological Measurement. Her research is typically generated by practical testing problems and has focused on a wide variety of issues, including linking and concordance. Dr. Paul W. Holland is the Frederic M. Lord Chair in Measurement and Statistics at Educational Testing Service and before that professor in the School of Education and the department of Statistics at the University of California, Berkeley. His books include Discrete Multivariate Analysis, Differential Item Functioning, Perspectives on Social Network Research , and two books on test score equating. He is a fellow of the American Statistical Association and the Institute for Mathematical Statistics, was designated a National Associate of the National Academies, was awarded for his career contributions by the National Council on Measurement in Education, and was elected to the National Academy of Education Nota de contenido: Overview -- Overview -- Foundations -- A Framework and History for Score Linking -- Data Collection Designs and Linking Procedures -- Equating -- Equating: Best Practices and Challenges to Best Practices -- Practical Problems in Equating Test Scores: A Practitioner’s Perspective -- Potential Solutions to Practical Equating Issues -- Tests in Transition -- Score Linking Issues Related to Test Content Changes -- Linking Scores Derived Under Different Modes of Test Administration -- Tests in Transition: Discussion and Synthesis -- Concordance -- Sizing Up Linkages -- Concordance: The Good, the Bad, and the Ugly -- Some Further Thoughts on Concordance -- Vertical Scaling -- Practical Issues in Vertical Scaling -- Methods and Models for Vertical Scaling -- Vertical Scaling and No Child Left Behind -- Assessments Linking Group Assessments to Individual -- Linking Assessments Based on Aggregate Reporting: Background and Issues -- An Enhanced Method for Mapping State Standards onto the NAEP Scale -- Using Aggregate-Level Linkages for Estimation and Validation: Comments on Thissen and Braun & Qian -- Postscript En línea: http://dx.doi.org/10.1007/978-0-387-49771-6 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=34496 Linking and Aligning Scores and Scales [documento electrónico] / SpringerLink (Online service) ; Neil J. Dorans ; Mary Pommerich ; Paul W. Holland . - New York, NY : Springer New York, 2007 . - XX, 396 p : online resource. - (Statistics for Social and Behavioral Sciences, ISSN 2199-7357) .
ISBN : 978-0-387-49771-6
Idioma : Inglés (eng)
Palabras clave: Statistics Assessment Psychology Methodology Psychological measurement Psychometrics for Social Science, Behavorial Education, Public Policy, and Law Assessment, Testing Evaluation Methods/Evaluation Clasificación: 51 Matemáticas Resumen: The comparability of measurements made in differing circumstances by different methods and investigators is a fundamental pre-condition for all of science. Successful applications of technology require comparable measurements. While the applications herefocus on educational tests, score linking issues are directly applicable to medicine and many branches of behavioral science. Since the 1980s, the fields of educational and psychological measurement have enhanced and widely applied techniques for producing linked scores that are comparable. The interpretation attached to a linkage depends on how the conditions of the linkage differ from the ideal. In this book, experts in statistics and psychometrics describe classes of linkages, the history of score linkings, data collection designs, and methods used to achieve sound score linkages. They describe and critically discuss applications to a variety of domains including equating of achievement exams, linkages between computer-delivered exams and paper-and-pencil exams, concordances between the current version of the SAT® and its predecessor, concordances between the ACT® and the SAT®, vertical linkages of exams that span grade levels, and linkages of scales from high-stakes state assessments to the scales of the National Assessment of Educational Progress (NAEP). Dr. Neil J. Dorans is a Distinguished Presidential Appointee at Educational Testing Service. During his 27 years at ETS, he has had primary responsibility for the statistical work associated with the AP®, PSAT/NMSQT®, and SAT® exams. He was the architect for the recentered SAT scales. He has guest edited special issues on score linking for Applied Measurement in Education, Applied Psychological Measurement, and the Journal of Educational Measurement. Dr. Mary Pommerich is a psychometrician in the Personnel Testing Division of the Defense Manpower Data Center, where she works with the ASVAB (Armed Services Vocational Aptitude Battery) testing program. She guest edited a special issue on concordance for Applied Psychological Measurement. Her research is typically generated by practical testing problems and has focused on a wide variety of issues, including linking and concordance. Dr. Paul W. Holland is the Frederic M. Lord Chair in Measurement and Statistics at Educational Testing Service and before that professor in the School of Education and the department of Statistics at the University of California, Berkeley. His books include Discrete Multivariate Analysis, Differential Item Functioning, Perspectives on Social Network Research , and two books on test score equating. He is a fellow of the American Statistical Association and the Institute for Mathematical Statistics, was designated a National Associate of the National Academies, was awarded for his career contributions by the National Council on Measurement in Education, and was elected to the National Academy of Education Nota de contenido: Overview -- Overview -- Foundations -- A Framework and History for Score Linking -- Data Collection Designs and Linking Procedures -- Equating -- Equating: Best Practices and Challenges to Best Practices -- Practical Problems in Equating Test Scores: A Practitioner’s Perspective -- Potential Solutions to Practical Equating Issues -- Tests in Transition -- Score Linking Issues Related to Test Content Changes -- Linking Scores Derived Under Different Modes of Test Administration -- Tests in Transition: Discussion and Synthesis -- Concordance -- Sizing Up Linkages -- Concordance: The Good, the Bad, and the Ugly -- Some Further Thoughts on Concordance -- Vertical Scaling -- Practical Issues in Vertical Scaling -- Methods and Models for Vertical Scaling -- Vertical Scaling and No Child Left Behind -- Assessments Linking Group Assessments to Individual -- Linking Assessments Based on Aggregate Reporting: Background and Issues -- An Enhanced Method for Mapping State Standards onto the NAEP Scale -- Using Aggregate-Level Linkages for Estimation and Validation: Comments on Thissen and Braun & Qian -- Postscript En línea: http://dx.doi.org/10.1007/978-0-387-49771-6 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=34496 Ejemplares
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Título : Multidimensional Item Response Theory Tipo de documento: documento electrónico Autores: M. D. Reckase ; SpringerLink (Online service) Editorial: New York, NY : Springer New York Fecha de publicación: 2009 Colección: Statistics for Social and Behavioral Sciences, ISSN 2199-7357 Número de páginas: X, 354 p Il.: online resource ISBN/ISSN/DL: 978-0-387-89976-3 Idioma : Inglés (eng) Palabras clave: Statistics Computer simulation Social sciences Psychology Methodology Psychological measurement Psychometrics for Science, Behavorial Education, Public Policy, and Law Simulation Modeling Methods/Evaluation of the Sciences Clasificación: 51 Matemáticas Resumen: Multidimensional Item Response Theory is the first book to give thorough coverage to this emerging area of psychometrics. The book describes the commonly used multidimensional item response theory (MIRT) models and the important methods needed for their practical application. These methods include ways to determine the number of dimensions required to adequately model data, procedures for estimating model parameters, ways to define the space for a MIRT model, and procedures for transforming calibrations from different samples to put them in the same space. A full chapter is devoted to methods for multidimensional computerized adaptive testing. The text is appropriate for an advanced course in psychometric theory or as a reference work for those interested in applying MIRT methodology. A working knowledge of unidimensional item response theory and matrix algebra is assumed. Knowledge of factor analysis is also helpful. Mark D. Reckase is a professor of Measurement and Quantitative Methods in the College of Education at Michigan State University. He has been president of the National Council of Measurement in Education, Vice President of Division D of the American Educational Research Association, on the Board of Trustees of the Psychometric Society, and the editor of Applied Psychological Measurement and the Journal of Educational Measurement. He has been doing research in the area of MIRT since 1972 Nota de contenido: Unidimensional Item Response Theory Models -- Historical Background for Multidimensional Item Response Theory (MIRT) -- Multidimensional Item Response Theory Models -- Statistical Descriptions of Item and Test Functioning -- Estimation of Item and Person Parameters -- Analyzing the Structure of Test Data -- Transforming Parameter Estimates to a Specified Coordinate System -- Linking and Scaling -- Computerized Adaptive Testing Using MIRT En línea: http://dx.doi.org/10.1007/978-0-387-89976-3 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33921 Multidimensional Item Response Theory [documento electrónico] / M. D. Reckase ; SpringerLink (Online service) . - New York, NY : Springer New York, 2009 . - X, 354 p : online resource. - (Statistics for Social and Behavioral Sciences, ISSN 2199-7357) .
ISBN : 978-0-387-89976-3
Idioma : Inglés (eng)
Palabras clave: Statistics Computer simulation Social sciences Psychology Methodology Psychological measurement Psychometrics for Science, Behavorial Education, Public Policy, and Law Simulation Modeling Methods/Evaluation of the Sciences Clasificación: 51 Matemáticas Resumen: Multidimensional Item Response Theory is the first book to give thorough coverage to this emerging area of psychometrics. The book describes the commonly used multidimensional item response theory (MIRT) models and the important methods needed for their practical application. These methods include ways to determine the number of dimensions required to adequately model data, procedures for estimating model parameters, ways to define the space for a MIRT model, and procedures for transforming calibrations from different samples to put them in the same space. A full chapter is devoted to methods for multidimensional computerized adaptive testing. The text is appropriate for an advanced course in psychometric theory or as a reference work for those interested in applying MIRT methodology. A working knowledge of unidimensional item response theory and matrix algebra is assumed. Knowledge of factor analysis is also helpful. Mark D. Reckase is a professor of Measurement and Quantitative Methods in the College of Education at Michigan State University. He has been president of the National Council of Measurement in Education, Vice President of Division D of the American Educational Research Association, on the Board of Trustees of the Psychometric Society, and the editor of Applied Psychological Measurement and the Journal of Educational Measurement. He has been doing research in the area of MIRT since 1972 Nota de contenido: Unidimensional Item Response Theory Models -- Historical Background for Multidimensional Item Response Theory (MIRT) -- Multidimensional Item Response Theory Models -- Statistical Descriptions of Item and Test Functioning -- Estimation of Item and Person Parameters -- Analyzing the Structure of Test Data -- Transforming Parameter Estimates to a Specified Coordinate System -- Linking and Scaling -- Computerized Adaptive Testing Using MIRT En línea: http://dx.doi.org/10.1007/978-0-387-89976-3 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33921 Ejemplares
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Título : New Developments in Quantitative Psychology : Presentations from the 77th Annual Psychometric Society Meeting Tipo de documento: documento electrónico Autores: SpringerLink (Online service) ; Roger E. Millsap ; L. Andries van der Ark ; Daniel M. Bolt ; Carol M. Woods Editorial: New York, NY : Springer New York Fecha de publicación: 2013 Otro editor: Imprint: Springer Colección: Springer Proceedings in Mathematics & Statistics, ISSN 2194-1009 num. 66 Número de páginas: IX, 506 p. 107 illus., 44 illus. in color Il.: online resource ISBN/ISSN/DL: 978-1-4614-9348-8 Idioma : Inglés (eng) Palabras clave: Statistics Psychology Methodology Psychological measurement Psychometrics for Social Science, Behavorial Education, Public Policy, and Law Methods/Evaluation Clasificación: 51 Matemáticas Resumen: The 77th Annual International Meeting of the Psychometric Society (IMPS) brought together quantitative researchers who focus on methods relevant to psychology. The conference included workshops, invited talks by well-known scholars, and presentations of submitted papers and posters. It was hosted by the University of Nebraska-Lincoln and took place between the 9th and 12th of July, 2012. The chapters of this volume are based on presentations from the meeting and reflect the latest work in the field. Topics with a primarily measurement focus include studies of item response theory, computerized adaptive testing, cognitive diagnostic modeling, and psychological scaling. Additional psychometric topics relate to structural equation modeling, factor analysis, causal modeling, mediation, missing data methods, and longitudinal data analysis, among others. The papers in this volume will be especially useful for researchers (graduate students and other quantitative researchers) in the social sciences who use quantitative methods, particularly psychologists. Most readers will benefit from some prior knowledge of statistical methods in reading the chapters Nota de contenido: Preface -- The Effect of Response Model Misspecification and Uncertainty on the Psychometric Properties of Estimates -- Heterogeneous Populations and Multistage Test Design -- Backmatter En línea: http://dx.doi.org/10.1007/978-1-4614-9348-8 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=32409 New Developments in Quantitative Psychology : Presentations from the 77th Annual Psychometric Society Meeting [documento electrónico] / SpringerLink (Online service) ; Roger E. Millsap ; L. Andries van der Ark ; Daniel M. Bolt ; Carol M. Woods . - New York, NY : Springer New York : Imprint: Springer, 2013 . - IX, 506 p. 107 illus., 44 illus. in color : online resource. - (Springer Proceedings in Mathematics & Statistics, ISSN 2194-1009; 66) .
ISBN : 978-1-4614-9348-8
Idioma : Inglés (eng)
Palabras clave: Statistics Psychology Methodology Psychological measurement Psychometrics for Social Science, Behavorial Education, Public Policy, and Law Methods/Evaluation Clasificación: 51 Matemáticas Resumen: The 77th Annual International Meeting of the Psychometric Society (IMPS) brought together quantitative researchers who focus on methods relevant to psychology. The conference included workshops, invited talks by well-known scholars, and presentations of submitted papers and posters. It was hosted by the University of Nebraska-Lincoln and took place between the 9th and 12th of July, 2012. The chapters of this volume are based on presentations from the meeting and reflect the latest work in the field. Topics with a primarily measurement focus include studies of item response theory, computerized adaptive testing, cognitive diagnostic modeling, and psychological scaling. Additional psychometric topics relate to structural equation modeling, factor analysis, causal modeling, mediation, missing data methods, and longitudinal data analysis, among others. The papers in this volume will be especially useful for researchers (graduate students and other quantitative researchers) in the social sciences who use quantitative methods, particularly psychologists. Most readers will benefit from some prior knowledge of statistical methods in reading the chapters Nota de contenido: Preface -- The Effect of Response Model Misspecification and Uncertainty on the Psychometric Properties of Estimates -- Heterogeneous Populations and Multistage Test Design -- Backmatter En línea: http://dx.doi.org/10.1007/978-1-4614-9348-8 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=32409 Ejemplares
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Título : Design of Observational Studies Tipo de documento: documento electrónico Autores: Paul R. Rosenbaum ; SpringerLink (Online service) Editorial: New York, NY : Springer New York Fecha de publicación: 2010 Colección: Springer Series in Statistics, ISSN 0172-7397 Número de páginas: XVIII, 384 p Il.: online resource ISBN/ISSN/DL: 978-1-4419-1213-8 Idioma : Inglés (eng) Palabras clave: Mathematics Biostatistics Probabilities Statistics Econometrics Social sciences Psychology Methodology Psychological measurement Probability Theory and Stochastic Processes Statistical Methods Methods/Evaluation of the Sciences Clasificación: 51 Matemáticas Resumen: An observational study is an empiric investigation of effects caused by treatments when randomized experimentation is unethical or infeasible. Observational studies are common in most fields that study the effects of treatments on people, including medicine, economics, epidemiology, education, psychology, political science and sociology. The quality and strength of evidence provided by an observational study is determined largely by its design. Design of Observational Studies is both an introduction to statistical inference in observational studies and a detailed discussion of the principles that guide the design of observational studies. Design of Observational Studies is divided into four parts. Chapters 2, 3, and 5 of Part I cover concisely, in about one hundred pages, many of the ideas discussed in Rosenbaum’s Observational Studies (also published by Springer) but in a less technical fashion. Part II discusses the practical aspects of using propensity scores and other tools to create a matched comparison that balances many covariates. Part II includes a chapter on matching in R. In Part III, the concept of design sensitivity is used to appraise the relative ability of competing designs to distinguish treatment effects from biases due to unmeasured covariates. Part IV discusses planning the analysis of an observational study, with particular reference to Sir Ronald Fisher’s striking advice for observational studies, "make your theories elaborate." Paul R. Rosenbaum is the Robert G. Putzel Professor of Statistics at the Wharton School of the University of Pennsylvania. He is a fellow of the American Statistical Association. In 2003, he received the George W. Snedecor Award from the Committee of Presidents of Statistical Societies. He is a senior fellow of the Leonard Davis Institute of Health Economics and a Research Associate at the Population Studies Center, both at the University of Pennsylvania. The second edition of his book, Observational Studies, was published by Springer in 2002 Nota de contenido: Beginnings -- Dilemmas and Craftsmanship -- Causal Inference in Randomized Experiments -- Two Simple Models for Observational Studies -- Competing Theories Structure Design -- Opportunities, Devices, and Instruments -- Transparency -- Matching -- A Matched Observational Study -- Basic Tools of Multivariate Matching -- Various Practical Issues in Matching -- Fine Balance -- Matching Without Groups -- Risk-Set Matching -- Matching in R -- Design Sensitivity -- The Power of a Sensitivity Analysis and Its Limit -- Heterogeneity and Causality -- Uncommon but Dramatic Responses to Treatment -- Anticipated Patterns of Response -- Planning Analysis -- After Matching, Before Analysis -- Planning the Analysis En línea: http://dx.doi.org/10.1007/978-1-4419-1213-8 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33584 Design of Observational Studies [documento electrónico] / Paul R. Rosenbaum ; SpringerLink (Online service) . - New York, NY : Springer New York, 2010 . - XVIII, 384 p : online resource. - (Springer Series in Statistics, ISSN 0172-7397) .
ISBN : 978-1-4419-1213-8
Idioma : Inglés (eng)
Palabras clave: Mathematics Biostatistics Probabilities Statistics Econometrics Social sciences Psychology Methodology Psychological measurement Probability Theory and Stochastic Processes Statistical Methods Methods/Evaluation of the Sciences Clasificación: 51 Matemáticas Resumen: An observational study is an empiric investigation of effects caused by treatments when randomized experimentation is unethical or infeasible. Observational studies are common in most fields that study the effects of treatments on people, including medicine, economics, epidemiology, education, psychology, political science and sociology. The quality and strength of evidence provided by an observational study is determined largely by its design. Design of Observational Studies is both an introduction to statistical inference in observational studies and a detailed discussion of the principles that guide the design of observational studies. Design of Observational Studies is divided into four parts. Chapters 2, 3, and 5 of Part I cover concisely, in about one hundred pages, many of the ideas discussed in Rosenbaum’s Observational Studies (also published by Springer) but in a less technical fashion. Part II discusses the practical aspects of using propensity scores and other tools to create a matched comparison that balances many covariates. Part II includes a chapter on matching in R. In Part III, the concept of design sensitivity is used to appraise the relative ability of competing designs to distinguish treatment effects from biases due to unmeasured covariates. Part IV discusses planning the analysis of an observational study, with particular reference to Sir Ronald Fisher’s striking advice for observational studies, "make your theories elaborate." Paul R. Rosenbaum is the Robert G. Putzel Professor of Statistics at the Wharton School of the University of Pennsylvania. He is a fellow of the American Statistical Association. In 2003, he received the George W. Snedecor Award from the Committee of Presidents of Statistical Societies. He is a senior fellow of the Leonard Davis Institute of Health Economics and a Research Associate at the Population Studies Center, both at the University of Pennsylvania. The second edition of his book, Observational Studies, was published by Springer in 2002 Nota de contenido: Beginnings -- Dilemmas and Craftsmanship -- Causal Inference in Randomized Experiments -- Two Simple Models for Observational Studies -- Competing Theories Structure Design -- Opportunities, Devices, and Instruments -- Transparency -- Matching -- A Matched Observational Study -- Basic Tools of Multivariate Matching -- Various Practical Issues in Matching -- Fine Balance -- Matching Without Groups -- Risk-Set Matching -- Matching in R -- Design Sensitivity -- The Power of a Sensitivity Analysis and Its Limit -- Heterogeneity and Causality -- Uncommon but Dramatic Responses to Treatment -- Anticipated Patterns of Response -- Planning Analysis -- After Matching, Before Analysis -- Planning the Analysis En línea: http://dx.doi.org/10.1007/978-1-4419-1213-8 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33584 Ejemplares
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