Trevor Bond, Zi Yan (HK The Education University of Hong Kong), Moritz Heene

Applying the Rasch Model

Fundamental Measurement in the Human Sciences

• Broschiertes Buch

Produktbeschreibung

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.

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Produktdetails

• Verlag: Taylor & Francis Ltd
• 4 ed
• Seitenzahl: 378
• Erscheinungstermin: 20. Juli 2020
• Englisch
• Abmessung: 254mm x 178mm x 20mm
• Gewicht: 694g
• ISBN-13: 9780367141424
• ISBN-10: 0367141426
• Artikelnr.: 59866252

Autorenporträt

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