Foreword Preface About the Authors Why Measurement Is Fundamental 1.1 Children Can Construct Measures 1.2 Interval scales v. ratio scales: A conceptual explanation 1.3 Statistics and/or Measurement 1.4 Why Fundamental Measurement? 1.5 Derived Measures 1.6 Conjoint Measurement 1.

7 The Rasch Model for Measurement 1.8 A More Suitable Analogy for Measurement in the Human Sciences 1.9 In Conclusion 1.10 Summary Important Principles of Measurement Made Explicit 2.1 An example: "By how much?" 2.2 Moving From Observations to Measures 2.3 The basic Rasch assumptions 2.4 Summary Basic Principles of the Rasch Model 3.

1 The Pathway Analogy 3.2 Unidimensionality 3.3 Item Fit 3.4 Difficulty/Ability Estimation and Error 3.5 Reliability 3.6 A Basic Framework for Measurement 3.7 Fit (Quality Control) 3.8 The Rasch Model 3.

9 Summary Building a Set of Items for Measurement 4.1 The Nature of the Data 4.2 Analyzing Dichotomous Data: The BLOT 4.3 A Simple Rasch Summary: The Item Pathway 4.4 Item Statistics 4.5 Item Fit 4.6 The Wright Map 4.7 Targeting 4.

8 Comparing Persons and Items 4.9 Summary 4.10 Extended Understanding--Chapter 4 4.11 The Problem of Guessing 4.12 Difficulty, Ability, and Fit 4.13 The Theory-Practice Dialogue 4.14 Summary Invariance: A Crucial Property of Scientific Measurement 5.1 Person and Item Invariance 5.

2 Common Item Linking 5.3 Anchoring Item Values 5.4 Vertical Scaling 5.5 Common-Person Linking 5.6 Invariance of Person Estimates Across Tests: Concurrent Validity 5.7 The PRTIII-Pendulum 5.8 Common-Person Linking 5.9 The Theory-Practice Dialogue 5.

10 Measurement Invariance: Where It Really Matters 5.11 Failures of Invariance: DIF 5.12 Differential Rater Functioning 5.13 DIF: Not just a problem, but an opportunity 5.14 Summary Measurement Using Likert Scales 6.1 The Rasch Model for Polytomous Data 6.2 Analyzing Rating Scale Data: The Instrumental Attitude towards Self-assessment Questionnaire 6.3 Item Ordering 6.

4 Targeting and Reliability 6.5 Summary 6.6 Extended Understanding--Chapter 6 6.7 Summary The Partial Credit Rasch Model 7.1 Clinical Interview Analysis: A Rasch-Inspired Breakthrough 7.2 Scoring Interview Transcripts 7.3 Partial Credit Model Results 7.4 Interpretation 7.

5 The Theory-Practice Dialogue 7.6 Unidimensionality 7.7 Summary 7.8 Extended Understanding--Chapter 7 7.9 Category Functioning 7.10 Point-Measure Correlations 7.11 Fit Statistics 7.12 Dimensionality: Primary Components Factor Analysis 7.

13 Summary Measuring Facets Beyond Ability and Difficulty 8.1 A Basic Introduction to the Many-Facets Rasch Model 8.2 Why Not Use Interrater Reliability? 8.3 Relations Among the Rasch Family of Models 8.4 Data Specifications of the Many-Facets Rasch Model 8.5 Rating Creativity of Junior Scientists 8.6 Many-Facets Analysis of Eighth-Grade Writing 8.7 Summary 8.

8 Extended Understanding--Chapter 8 8.9 Invariance of Rated Creativity Scores 8.10 Rasch Measurement of Facets Beyond Rater Effects 8.11 Summary Making Measures, Setting Standards, and Rasch Regression 9.1 Creating a Measure from Existing Data 9.2 Method 9.3 Physical Fitness Indicators 9.4 Data Analysis 9.

5 Seven Criteria to Investigate the Quality of Physical Fitness Indicators 9.6 Results and Discussion 9.7 Optimizing Response Categories 9.8 Influence of Underfitting Persons on the RMPFS 9.9 Properties of the RMPFS With Subsamples 9.10 Age Dependent or Age Related? 9.11 The Final Version of RMPFS 9.12 Objective Standard Setting: The OSS Model 9.

13 Early Definitions 9.14 The Objective Standard Setting Models 9.15 Objective Standard Setting for Dichotomous Examinations 9.16 Objective Standard Setting for Judge-Mediated Examinations 9.17 Fair Standards, Not Absolute Values 9.18 Rasch Regression 9.19 Predicting Physician Assistant Faculty Intention to Leave Academia 9.20 Rasch Regression Using the Anchored Formulation 9.

21 Rasch Regression: Alternative Approaches 9.22 Discussion 9.23 Summary The Rasch Model Applied Across the Human Sciences 10.1 Rasch Measurement in Health Sciences 10.2 Establishing Rasch psychometric properties: The A-ONE J 10.3 More than mere psychometric indicators: The PAM 10.4 Refining an existing instrument: The POSAS 10.5 Optimizing an existing instrument: The NIHSS and a central role for PCA 10.

6 Creating a Short Form of an Existing Instrument: The FSQ 10.7 Theory guides assessment revisions: The PEP-S8 10.8 Applications in Education and Psychology 10.9 Test development 10.10 The Goodenough Draw-a-Man Test: One Drawing is Good enough 10.11 Rasch Gain Calculations: Racking and Stacking 10.12 Rasch Learning Gain Calculations: The CCI 10.13 Racking and stacking 10.

14 Stacking can be enough: UPAM 10.15 Sub-test structure informs scoring models 10.16 Applications to classroom testing 10.17 Can Rasch measurement help S. S. Stevens? 10.18 Using Rasch Measures with Path Analysis (SEM framework) 10.19 Rasch person measures used in a partial least squares (PLS) framework 10.

20 And those Rasch measurement SEs? 10.21 Can we really combine SEM and Rasch models? 10.22 Conclusion 10.23 Summary Rasch Modeling Applied: Rating Scale Design 11.1 Rating Scale Design 11.2 Category Frequencies and Average Measures 11.3 Thresholds and Category Fit 11.4 Revising a Rating Scale 11.

5 An Example 11.6 Guidelines for Collapsing Categories 11.7 Problems With Negatively Worded Items 11.7 The Invariance of the Measures Across Groups 11.8 Summary Rasch Model Requirements: Model Fit and Unidimensionality 12.1 The Data, the Model, and the Residuals 12.2 Residuals 12.3 Fit Statistics 12.

4 Expectations of Variation 12.5 Fit, Misfit, and Interpretation 12.6 Fit: Issues for Resolution 12.7 Misfit: A Fundamental Issue 12.8 In the Interim 12.9 Detecting Multiple Dimensions 12.10 Linear Factor Analysis--Problems and Promise 12.11 Rasch Factor Analysis (PCA) 12.

12 Principal Components Analysis of Rasch Residuals--The BLOT as An Exemplar 12.13 One Dimension, Two Dimensions, Three Dimensions, More? 12.14 Extended Understanding--Chapter 12 12.15 A Further Investigation: BLOT and PRTIII 12.16 Summary A Synthetic Overview 13.1 Additive Conjoint Measurement--ACM 13.2 True Score Theory, Latent Traits, and Item Response Theory 13.3 Would You Like an Interval Scale With That? 13.

4 Model Assumptions and Measurement Requirements 13.5 Construct Validity 13.6 The Rasch Model and Progress of Science 13.7 Back to the Beginning and Back to the End 13.8 Summary Appendix A: Getting Started Appendix B: Technical Aspects of the Rasch Model Appendix C: Going All the Way Glossary Author Index Subject Index.