Applying the Rasch Model (4^th Ed.) 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 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

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

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.