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Recognised as the most influential publication in the field, ARM facilitates deep understanding of the Rasch model and its practical applications. The authors review the crucial properties of the model and demonstrate its use with examples across the human sciences.
Recognised as the most influential publication in the field, ARM facilitates deep understanding of the Rasch model and its practical applications. The authors review the crucial properties of the model and demonstrate its use with examples across the human sciences.
Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.
Trevor G. Bond is currently Adjunct Professor at the College of Arts, Society and Education at James Cook University, Australia.
Zi Yan is Associate Professor in the Department of Curriculum and Instruction at the Education University of Hong Kong.
Moritz Heene is Full Professor of Learning Sciences Research Methodologies (i.e., Quantitative Methods) at the Ludwig-Maximilians-Universität München, Germany.
Inhaltsangabe
Foreword Preface Notes on This Volume About the Authors 1. Why Measurement Is Fundamental Children Can Construct Measures Interval Scales v. Ratio Scales: A Conceptual Explanation Statistics and/or Measurement Why Fundamental Measurement? Derived Measures Conjoint Measurement The Rasch Model for Measurement A More Suitable Analogy for Measurement in the Human Sciences In Conclusion Summary 2. Important Principles of Measurement Made Explicit An example: "By How Much?" Moving From Observations to Measures Summary 3. Basic Principles of the Rasch Model The Pathway Analogy A Basic Framework for Measurement The Rasch Model Summary 4. Building a Set of Items for Measurement The Nature of the Data Analyzing Dichotomous Data: The BLOT A Simple Rasch Summary: The Item Pathway Item Statistics Item Fit The Wright Map Targeting Comparing Persons and Items Summary Extended Understanding The Problem of Guessing Difficulty, Ability, and Fit The Theory-Practice Dialog Summary 5. Invariance: A Crucial Property of Scientific Measurement Person and Item Invariance Common-Item Linking Please Keep in Mind Anchoring Item Values Vertical Scaling Common-Person Linking Invariance of Person Estimates across Tests: Concurrent Validity The PRTIII-Pendulum Common-Person Linking: BLOT & PRTIII The Theory-Practice Dialog Measurement Invariance: Where It Really Matters Failures of Invariance: DIF Differential Rater Functioning DIF: Not Just a Problem, but an Opportunity Summary 6. Measurement Using Likert Scales The Rasch Model for Polytomous Data Analyzing Rating Scale Data: The Instrumental Attitude towards Self-Assessment Questionnaire Summary Extended Understanding Summary 7. The Partial Credit Rasch Model Clinical Interview Analysis: A Rasch-Inspired Breakthrough Scoring Interview Transcripts Partial Credit Model Results Interpretation The Theory-Practice Dialog Summary Extended Understanding Point-Measure Correlations Fit Statistics Dimensionality: Primary Components Factor Analysis Summary 8. Measuring Facets Beyond Ability and Difficulty A Basic Introduction to the Many-Facets Rasch Model Why Not Use Interrater Reliability? Relations Among the Rasch Family of Models Data Specifications of the Many-Facets Rasch Model Rating Creativity of Junior Scientists 8.6 Many-Facets Analysis of Eighth-Grade Writing Summary Extended Understanding Rasch Measurement of Facets Beyond Rater Effects Summary 9. Making Measures, Setting Standards, and Rasch Regression Creating a Measure from Existing Data: The RMPFS (Zi Yan, EdUHK) Method: Data Physical Fitness Indicators Data Analysis Seven Criteria to Investigate the Quality of Physical Fitness Indicators Results and Discussion Optimising Response Categories Influence of Underfitting Persons on the RMPFS Properties of the RMPFS With Subsamples Age Dependent or Age Related? The Final Version of RMPFS Objective Standard Setting: The OSS Model (Gregory Stone, U Toledo) Early Definitions The Objective Standard Setting Models Objective Standard Setting for Dichotomous Examinations Objective Standard Setting for Judge-Mediated Examinations Fair Standards, Not Absolute Values Rasch Regression (Svetlana Beltyukova, U Toledo) Predicting Physician Assistant Faculty Intention to Leave Academia Rasch Regression Using the Anchored Formulation Rasch Regression: Alternative Approaches Discussion Summary 10. The Rasch Model Applied Across the Human Sciences Rasch Measurement in Health Sciences Optimising an Existing Instrument: The NIHSS and a Central Role for PCA Creating a Short Form of an Existing Instrument: The FSQ FSQ-SF Theory Guides Assessment Revisions: The PEP-S8 Applications in Education and Psychology Rasch Measures as Grist for the Analytical Mill Rasch Gain Calculations: Racking and Stacking Rasch Learning Gain Calculations: The CCI Racking and Stacking Stacking Can Be Enough: UPAM Sub- Test Structure Informs Scoring Models Applications to Classroom Testing Can Rasch Measurement Help S.S. Stevens? Using Rasch Measures with Path Analysis (SEM Framework) Rasch Person Measures Used in a Partial Least Squares (PLS) Framework And Those Rasch Measurement SEs? Can We Really Combine SEM and Rasch Models? Conclusion Summary 11. Rasch Modeling Applied: Rating Scale Design Rating Scale Design Category Frequencies and Average Measures Thresholds and Category Fit Revising a Rating Scale An Example Guidelines for Collapsing Categories Problems With Negatively Worded Items The Invariance of the Measures across Groups Summary 12. Rasch Model Requirements: Model Fit and Unidimensionality The Data, the Model, and the Residuals Residuals Fit Statistics Expectations of Variation Fit, Misfit, and Interpretation Fit: Issues for Resolution Principal Components Analysis of Rasch Residuals: The BLOT as an Exemplar One Dimension, Two Dimensions, Three Dimensions, More? Extended Understanding A Further Investigation: BLOT and PRTIII Summary 13. A Synthetic Overview Additive Conjoint Measurement (ACM) True Score Theory, Latent Traits, and Item Response Theory Would You Like an Interval Scale With That? Model Assumptions and Measurement Requirements Construct Validity The Rasch Model and Progress of Science Back to the Beginning and Back to the End Summary Appendix A: Getting Started Appendix B: Technical Aspects of the Rasch Model Appendix C: Going All the Way Glossary Author Index Subject Index
Foreword Preface Notes on This Volume About the Authors 1. Why Measurement Is Fundamental Children Can Construct Measures Interval Scales v. Ratio Scales: A Conceptual Explanation Statistics and/or Measurement Why Fundamental Measurement? Derived Measures Conjoint Measurement The Rasch Model for Measurement A More Suitable Analogy for Measurement in the Human Sciences In Conclusion Summary 2. Important Principles of Measurement Made Explicit An example: "By How Much?" Moving From Observations to Measures Summary 3. Basic Principles of the Rasch Model The Pathway Analogy A Basic Framework for Measurement The Rasch Model Summary 4. Building a Set of Items for Measurement The Nature of the Data Analyzing Dichotomous Data: The BLOT A Simple Rasch Summary: The Item Pathway Item Statistics Item Fit The Wright Map Targeting Comparing Persons and Items Summary Extended Understanding The Problem of Guessing Difficulty, Ability, and Fit The Theory-Practice Dialog Summary 5. Invariance: A Crucial Property of Scientific Measurement Person and Item Invariance Common-Item Linking Please Keep in Mind Anchoring Item Values Vertical Scaling Common-Person Linking Invariance of Person Estimates across Tests: Concurrent Validity The PRTIII-Pendulum Common-Person Linking: BLOT & PRTIII The Theory-Practice Dialog Measurement Invariance: Where It Really Matters Failures of Invariance: DIF Differential Rater Functioning DIF: Not Just a Problem, but an Opportunity Summary 6. Measurement Using Likert Scales The Rasch Model for Polytomous Data Analyzing Rating Scale Data: The Instrumental Attitude towards Self-Assessment Questionnaire Summary Extended Understanding Summary 7. The Partial Credit Rasch Model Clinical Interview Analysis: A Rasch-Inspired Breakthrough Scoring Interview Transcripts Partial Credit Model Results Interpretation The Theory-Practice Dialog Summary Extended Understanding Point-Measure Correlations Fit Statistics Dimensionality: Primary Components Factor Analysis Summary 8. Measuring Facets Beyond Ability and Difficulty A Basic Introduction to the Many-Facets Rasch Model Why Not Use Interrater Reliability? Relations Among the Rasch Family of Models Data Specifications of the Many-Facets Rasch Model Rating Creativity of Junior Scientists 8.6 Many-Facets Analysis of Eighth-Grade Writing Summary Extended Understanding Rasch Measurement of Facets Beyond Rater Effects Summary 9. Making Measures, Setting Standards, and Rasch Regression Creating a Measure from Existing Data: The RMPFS (Zi Yan, EdUHK) Method: Data Physical Fitness Indicators Data Analysis Seven Criteria to Investigate the Quality of Physical Fitness Indicators Results and Discussion Optimising Response Categories Influence of Underfitting Persons on the RMPFS Properties of the RMPFS With Subsamples Age Dependent or Age Related? The Final Version of RMPFS Objective Standard Setting: The OSS Model (Gregory Stone, U Toledo) Early Definitions The Objective Standard Setting Models Objective Standard Setting for Dichotomous Examinations Objective Standard Setting for Judge-Mediated Examinations Fair Standards, Not Absolute Values Rasch Regression (Svetlana Beltyukova, U Toledo) Predicting Physician Assistant Faculty Intention to Leave Academia Rasch Regression Using the Anchored Formulation Rasch Regression: Alternative Approaches Discussion Summary 10. The Rasch Model Applied Across the Human Sciences Rasch Measurement in Health Sciences Optimising an Existing Instrument: The NIHSS and a Central Role for PCA Creating a Short Form of an Existing Instrument: The FSQ FSQ-SF Theory Guides Assessment Revisions: The PEP-S8 Applications in Education and Psychology Rasch Measures as Grist for the Analytical Mill Rasch Gain Calculations: Racking and Stacking Rasch Learning Gain Calculations: The CCI Racking and Stacking Stacking Can Be Enough: UPAM Sub- Test Structure Informs Scoring Models Applications to Classroom Testing Can Rasch Measurement Help S.S. Stevens? Using Rasch Measures with Path Analysis (SEM Framework) Rasch Person Measures Used in a Partial Least Squares (PLS) Framework And Those Rasch Measurement SEs? Can We Really Combine SEM and Rasch Models? Conclusion Summary 11. Rasch Modeling Applied: Rating Scale Design Rating Scale Design Category Frequencies and Average Measures Thresholds and Category Fit Revising a Rating Scale An Example Guidelines for Collapsing Categories Problems With Negatively Worded Items The Invariance of the Measures across Groups Summary 12. Rasch Model Requirements: Model Fit and Unidimensionality The Data, the Model, and the Residuals Residuals Fit Statistics Expectations of Variation Fit, Misfit, and Interpretation Fit: Issues for Resolution Principal Components Analysis of Rasch Residuals: The BLOT as an Exemplar One Dimension, Two Dimensions, Three Dimensions, More? Extended Understanding A Further Investigation: BLOT and PRTIII Summary 13. A Synthetic Overview Additive Conjoint Measurement (ACM) True Score Theory, Latent Traits, and Item Response Theory Would You Like an Interval Scale With That? Model Assumptions and Measurement Requirements Construct Validity The Rasch Model and Progress of Science Back to the Beginning and Back to the End Summary Appendix A: Getting Started Appendix B: Technical Aspects of the Rasch Model Appendix C: Going All the Way Glossary Author Index Subject Index
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