Applying the Rasch Model Fundamental Measurement in 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. Readers will be able to understan...
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| Abstract | 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. Readers will be able to understand and critically evaluate Rasch measurement research, perform their own Rasch analyses and interpret their results. The glossary and illustrations support that understanding, and the accessible approach means that it is ideal for readers without a mathematical background.
Intended as a text for graduate courses in measurement, item response theory, (advanced) research methods or quantitative analysis taught in psychology, education, human development, business and other social and health sciences. Professionals in these areas will also appreciate the book’s accessible introduction.
Highlights of the new edition include:
More learning tools to strengthen readers’ understanding including chapter introductions, boldfaced key terms, chapter summaries, activities and suggested readings.
Greater emphasis on the use of R packages; readers can download the R code from the Routledge website.
Explores the distinction between numerical values, quantity and units, to understand the measurement and the role of the Rasch logit scale (Chapter 4).
A new four-option data set from the IASQ (Instrumental Attitude toward Self-assessment Questionnaire) for the Rating Scale Model (RSM) analysis exemplar (Chapter 6).
Clarifies the relationship between Rasch measurement, path analysis and SEM, with a host of new examples of Rasch measurement applied across health sciences, education and psychology (Chapter 10). |
|---|---|
| AbstractList | 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. Readers will be able to understand and critically evaluate Rasch measurement research, perform their own Rasch analyses and interpret their results. The glossary and illustrations support that understanding, and the accessible approach means that it is ideal for readers without a mathematical background.Highlights of the new edition include:More learning tools to strengthen readers' understanding including chapter introductions, boldfaced key terms, chapter summaries, activities and suggested readings. Greater emphasis on the use of R packages; readers can download the R code from the Routledge website. Explores the distinction between numerical values, quantity and units, to understand the measurement and the role of the Rasch logit scale (Chapter 4).A new four-option data set from the IASQ (Instrumental Attitude towards Self-assessment Questionnaire) for the Rating Scale Model (RSM) analysis exemplar (Chapter 6). Clarifies the relationship between Rasch measurement, path analysis and SEM, with a host of new examples of Rasch measurement applied across health sciences, education and psychology (Chapter 10). Intended as a text for graduate courses in measurement, item response theory, (advanced) research methods or quantitative analysis taught in psychology, education, human development, business, and other social and health sciences. Professionals in these areas will also appreciate the book's accessible introduction. 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. Readers will be able to understand and critically evaluate Rasch measurement research, perform their own Rasch analyses and interpret their results. The glossary and illustrations support that understanding, and the accessible approach means that it is ideal for readers without a mathematical background. Highlights of the new edition include: More learning tools to strengthen readers’ understanding including chapter introductions, boldfaced key terms, chapter summaries, activities and suggested readings. Greater emphasis on the use of R packages; readers can download the R code from the Routledge website. Explores the distinction between numerical values, quantity and units, to understand the measurement and the role of the Rasch logit scale (Chapter 4). A new four-option data set from the IASQ (Instrumental Attitude towards Self-assessment Questionnaire) for the Rating Scale Model (RSM) analysis exemplar (Chapter 6). Clarifies the relationship between Rasch measurement, path analysis and SEM, with a host of new examples of Rasch measurement applied across health sciences, education and psychology (Chapter 10). Intended as a text for graduate courses in measurement, item response theory, (advanced) research methods or quantitative analysis taught in psychology, education, human development, business, and other social and health sciences. Professionals in these areas will also appreciate the book’s accessible introduction. Foreword Preface Notes on This Volume About the Authors 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 Important Principles of Measurement Made Explicit An example: "By How Much?" Moving From Observations to Measures Summary Basic Principles of the Rasch Model The Pathway Analogy A Basic Framework for Measurement The Rasch Model Summary 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 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 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 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 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 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 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 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 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 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 From a previous edition: "The tiresome debate about Rasch vs. IRT is over – if you want to construct valid measurements from uncertain observations you need to understand and learn how to use Rasch measurement. Bond and Fox is your huckleberry – read it and get to work!" – Robert W. Massof, Johns Hopkins University School of Medicine, USA "Bond & Fox's book is a must read for anyone interested in measurement. This book is my go-to for introducing graduate students to the Rasch model." – Kelly D. Bradley, University of Kentucky, USA "The authors have successfully made sophisticated measurement theory into feasible practice for practitioners by providing clear and intuitive explanations, numerous examples, and nice computer outputs. It is a textbook that I have used and will continue to use in the future." – Wen Chung Wang, Hong Kong Institute of Education, Hong Kong "The Rasch model represents modern measurement theory at its best … Rasch models are used around the world to create psychometrically defensible scales and tests. Bond and Fox provide an accessible introduction to the Rasch model that describes the logic and essential importance of fundamental measurement in the human sciences." – George Engelhard, Jr., The University of Georgia, USA 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. 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. Readers will be able to understand and critically evaluate Rasch measurement research, perform their own Rasch analyses and interpret their results. The glossary and illustrations support that understanding, and the accessible approach means that it is ideal for readers without a mathematical background. Intended as a text for graduate courses in measurement, item response theory, (advanced) research methods or quantitative analysis taught in psychology, education, human development, business, and other social and health sciences. Professionals in these areas will also appreciate the book's accessible introduction. [Publisher summary, ed] 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. Readers will be able to understand and critically evaluate Rasch measurement research, perform their own Rasch analyses and interpret their results. The glossary and illustrations support that understanding, and the accessible approach means that it is ideal for readers without a mathematical background. Intended as a text for graduate courses in measurement, item response theory, (advanced) research methods or quantitative analysis taught in psychology, education, human development, business and other social and health sciences. Professionals in these areas will also appreciate the book’s accessible introduction. Highlights of the new edition include: More learning tools to strengthen readers’ understanding including chapter introductions, boldfaced key terms, chapter summaries, activities and suggested readings. Greater emphasis on the use of R packages; readers can download the R code from the Routledge website. Explores the distinction between numerical values, quantity and units, to understand the measurement and the role of the Rasch logit scale (Chapter 4). A new four-option data set from the IASQ (Instrumental Attitude toward Self-assessment Questionnaire) for the Rating Scale Model (RSM) analysis exemplar (Chapter 6). Clarifies the relationship between Rasch measurement, path analysis and SEM, with a host of new examples of Rasch measurement applied across health sciences, education and psychology (Chapter 10). 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. |
| Author | Moritz Heene Trevor Bond Zi Yan |
| AuthorAffiliation | University of Hong Kong Universitat Munchen James Cook University |
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| Keywords | Ability Estimates Point Measure Correlations Multidimensional Rasch Model Rasch Analysis Category Probability Curves Item Difficulty Estimates Multidimensional Random Coefficients Multinomial Logit Logit Scale Wright Map Conjoint Measurement DIF Additive Conjoint Measurement Item Estimate Rasch Model Rasch Measurement Rasch Dimension Person Ability Estimates Misfitting Items RSM Item Difficulty Polytomous Data Fit Statistics Item Person Map Rasch Model’s Expectation Rasch Residuals |
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| Notes | Removed invalid ISBN/suffix "(pbk)". London: Routledge, July 2020. Includes bibliographical references. xxvii, 348p. |
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| SubjectTerms | ability analysis Business education difficulties difficulty estimate estimates fit item Item response theory measurement Measurement techniques Medical Statistics Psychological Methods & Statistics Psychology Psychology-Research-Methodology Psychology-Statistical methods Rasch model Research Methods for Social and Behavioral Sciences Research Methods in Education Social sciences Social sciences-Research-Methodology Social sciences-Statistical methods statistics Teaching models Testing, Measurement and Assessment |
| Subtitle | Fundamental Measurement in the Human Sciences |
| TableOfContents | Interpretation -- Extended Understanding -- Working with Excel and SPSS Data Files -- Further Analyses -- Next Steps -- The Classic Reference Texts -- Journal of Applied Measurement -- www.rasch.org -- Start Reading Rasch Research and Methods for Free -- Computer Software for Rasch Measurement -- eRm: Extended Rasch Modeling -- Appendix B: Technical Aspects of the Rasch Model -- Rasch Family of Models -- Dichotomous Model -- Parameter Separation -- Rating-Scale Model -- Partial Credit Model -- Many-Facets Rasch Model -- Rasch Model Assessment -- Reliability Indices -- Test Information -- Fit Statistics -- Appendix C: Going All the Way -- Absence of Evidence Is Not Evidence for Absence -- What Are the Weaknesses of Residual-Based Statistics? -- Testing the Requirement of Equal Item Slopes: Global Model Tests and Model Fit Comparisons -- Using Confirmatory Factor Analysis to Test the Equality of Item Slopes -- Using Test Analysis Modules (TAM) to Test the Equality of Item Slopes -- Using the Andersen Likelihood Ratio Test and the Rasch Graphical Model Check to Test the Equality of Item Slopes -- Testing Dimensionality Using Structural Equation Modeling -- Conclusion -- Note -- References -- Glossary -- Author Index -- Subject Index Failures of Invariance: DIF -- Differential Rater Functioning -- DIF: Not Just a Problem, but an Opportunity -- Summary -- References -- 6 Measurement Using Likert Scales -- The Rasch Model for Polytomous Data -- Analyzing Rating Scale Data: The Instrumental Attitude toward Self-Assessment Questionnaire -- Item Ordering -- Targeting and Reliability -- Summary -- Extended Understanding -- Item Polarity -- Empirical Item-Category Measures -- Category Function -- Dimensionality Map -- Item Misfit Table -- Construct KeyMap -- Person Misfit Table -- Separation Table -- Summary -- Notes -- References -- 7 The Partial Credit Rasch Model -- Clinical Interview Analysis: A Rasch-Inspired Breakthrough -- Scoring Interview Transcripts -- Ordered Performance Criteria for 18 Aspects of the Pendulum Interview Task -- Partial Credit Model Results -- Interpretation -- The Theory-Practice Dialog -- Unidimensionality -- Summary -- ARMsteps -- Extended Understanding -- Category Functioning -- Point-Measure Correlations -- Fit Statistics -- Dimensionality: Primary Components Factor Analysis of the Rasch Residuals -- Summary -- Note -- References -- 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 -- Many-Facets Analysis of Eighth-Grade Writing -- Summary -- Extended Understanding -- Invariance of Rated Creativity Scores -- Rasch Measurement of Facets Beyond Rater Effects -- Summary -- References -- 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 Cover -- Half Title -- Title Page -- Copyright Page -- Dedication -- Table of contents -- Figures -- Tables -- About the Authors -- Foreword -- Preface -- Notes on This Volume -- Acknowledgments -- 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 -- Note -- Suggested Readings -- References -- 2 Important Principles of Measurement Made Explicit -- An Example: "By How Much?" -- Moving from Observations to Measures -- Summary -- Notes -- Suggested Readings -- References -- 3 Basic Principles of the Rasch Model -- The Pathway Analogy -- Unidimensionality -- Item Fit -- Difficulty/Ability Estimation and Error -- Reliability -- A Basic Framework for Measurement -- Fit (Quality Control) -- The Rasch Model -- Summary -- References -- 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 -- References -- 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 Seven Criteria to Investigate the Quality of Physical Fitness Indicators -- Results and Discussion -- Consideration of BMI -- Consideration of Sit-and-Reach -- Consideration of Handgrip -- Consideration of Push-Ups -- 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 -- References -- 10 The Rasch Model Applied across the Human Sciences -- Rasch Measurement in Health Sciences -- Establishing Rasch Psychometric Properties: The A-ONE J -- More Than Mere Psychometric Indicators: The PAM -- Refining an Existing Instrument: The POSAS -- 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 -- Test Development -- The Goodenough Draw-a-Man Test: One Drawing Is Good Enough -- 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 -- References -- 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 -- Suggested Readings -- References -- 12 Rasch Model Requirements Model Fit and Unidimensionality -- 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 -- Misfit: A Fundamental Issue -- In the Interim -- Detecting Multiple Dimensions -- Linear Factor Analysis: Problems and Promise -- Rasch Factor Analysis (PCA) -- 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 -- References -- 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 -- Note -- References -- Appendix A -- Getting Started -- Data Input -- Software -- First Analysis -- Output -- What to Look For -- Where to Look -- The Wright Map -- The Item Statistics Table -- Case Statistics Table -- Next Steps -- The Pathway Map |
| Title | Applying the Rasch Model |
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