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• Preface
• Acknowledgments
• About the Authors
• Chapter 1 • Overview
• General Perspectives on Measurement
• Historical Origins of Measurement in Social Science
• Early Examples
• Emergence of Statistical Methods and the Role of Mental Testing
• The Role of Psychophysics
• Later Developments in Measurement
• Evolution of Basic Concepts
• Evolution of Mental Testing
• Assessment of Mental Illness
• Broadening the Domain of Psychometrics
• The Role of Measurement in the Social Sciences
• The Relationship of Theory to Measurement
• Theoretical and Atheoretical Measures
• Composite Measurement Tools
• All Scales Are Not Created Equal
• Costs of Poor Measurement
• Summary and Preview
• Exercises
• Chapter 2 • Understanding the Latent Variable
• Constructs Versus Measures
• Latent Variable as the Presumed Cause of Scale Item Values
• Path Diagrams
• Diagrammatic Conventions
• Path Diagrams in Scale Development
• Further Elaboration of the Measurement Model
• Classical Measurement Assumptions
• Parallel Tests
• Alternative Models
• Choosing a Causal Model
• Exercises
• Note
• Chapter 3 • Scale Reliability
• Methods Based on the Analysis of Variance
• Continuous Versus Dichotomous Items
• Internal Consistency
• Coefficient Alpha
• The Covariance Matrix
• Covariance Matrices for Multi-Item Scales
• Alpha and the Covariance Matrix
• Alternative Formula for Alpha
• Critique of Alpha
• Remedies to Alpha’s Limitations
• Coefficient Omega (ω)
• Reliability Based on Correlations Between Scale Scores
• Alternate-Forms Reliability
• Split-Half Reliability
• Inter-Rater Agreement
• Temporal Stability
• Reliability of Change Scores
• Reliability and Statistical Power
• Generalizability Theory
• Summary
• Exercises
• Notes
• Chapter 4 • Scale Validity
• Content Validity
• Scope of the Variable and Implications for Content Validity
• Criterion-Related Validity
• Criterion-Related Validity Versus Accuracy
• Construct Validity
• Differentiating Construct From Criterion-Related Validity
• Attenuation
• How Strong Should Correlations Be to Demonstrate Construct Validity?
• Multitrait-Multimethod Matrix
• What About Face Validity?
• Exercises
• Chapter 5 • Guidelines in Scale Development
• Step 1: Determine Clearly What It Is You Want to Measure
• Theory as an Aid to Clarity
• Specificity as an Aid to Clarity
• Being Clear About What to Include in a Measure
• Step 2: Generate an Item Pool
• Choose Items That Reflect the Scale’s Purpose
• Redundancy
• Number of Items
• Beginning the Process of Writing Items
• Characteristics of Good and Bad Items
• Positively and Negatively Worded Items
• Conclusion
• Step 3: Determine the Format for Measurement
• Thurstone Scaling
• Guttman Scaling
• Scales With Equally Weighted Items
• How Many Response Categories?
• Specific Types of Response Formats
• Likert Scale
• Semantic Differential
• Visual Analog
• Pictorial Response Options
• Numerical Response Formats and Basic Neural Processes
• Binary Options
• Item Time Frames
• Mode of Administration
• Step 4: Have Initial Item Pool Reviewed by Experts
• Step 5: Cognitive Interviewing
• Step 6: Consider Inclusion of Validation Items
• Step 7: Administer Items to a Development Sample
• Step 8: Evaluate the Items
• Initial Examination of Items’ Performance
• Reverse Scoring
• Item-Scale Correlations
• Item Variances
• Item Means
• Dimensionality
• Reliability
• Step 9: Optimize Scale Length
• Effect of Scale Length on Reliability
• Effects of Dropping “Bad” Items
• Tinkering With Scale Length
• Split Samples
• Exercises
• Note
• Chapter 6 • Factor Analysis
• Overview of Factor Analysis
• Examples of Methods Analogous to Factor Analytic Concepts
• Example 1
• Example 2
• Shortcomings of These Methods
• Conceptual Description of Factor Analysis
• Extracting Factors
• The First Factor
• Subsequent Factors
• Deciding How Many Factors to Extract
• Rotating Factors
• Rotation Analogy 1
• Rotation Analogy 2
• Rotation Analogy 3
• Orthogonal Versus Oblique Rotation
• Choosing Type of Rotation
• Bifactor and Hierarchical Factor Models
• Interpreting Factors
• Principal Components Versus Common Factors
• Same or Different?
• Confirmatory Factor Analysis
• Using Factor Analysis in Scale Development
• Sample Size
• Conclusion
• Exercises
• Chapter 7 • The Index
• How an Index Differs From a Scale
• The Two Distinct Types of Index
• Causal Formative Measures
• Composite Formative Measures
• Other Conceptual Differences Between Scales and Indices
• Empirical Differences Between Scales and Indices
• Relationships Among Indicators
• Impact of Adding Items
• Rules of Thumb for Differentiating an Index From a Scale
• Limitations of Conceptual Criteria
• Limitations of Empirical Criteria
• Is It a Scale or an Index? Formal Methods for Distinguishing Effect and Causal Indicators
• The Correlation Matrix
• Factor Analysis
• Vanishing Tetrads
• Steps in Developing and Evaluating an Index
• Index Item Development
• The Role of Theory
• Index Item Creation
• Index Item Redundancy and Number
• Other Index Development Considerations
• Evaluating Items
• Regression as a Heuristic for Index Development
• Regression as an Alternative to Index Development
• Regression as a Method for Index Development and Validation
• Regression-Based Examples
• Index Validity
• Content Validity
• Construct Validity
• Criterion Validity
• Group Comparison Approach
• Index Reliability
• Hybrid Measures
• Hierarchical Hybrids
• Hierarchical Hybrid Indices and Multidimensional Scales
• Hybrids Involving Nonhierarchical Heterogeneous Indicators
• Methods Based on Structural Equation Modeling
• Heuristic Overview of Structural Equation Modeling
• MIMIC Models
• Criticisms of Index Composites
• Exercises
• Note
• Chapter 8 • An Overview of Item Response Theory
• Item Difficulty
• Item Discrimination
• Guessing, or False Positives
• Item-Characteristic Curves
• IRT Applied to Multiresponse Items
• Theta and Computerized Adaptive Testing (CAT)
• Complexities of IRT
• Conclusions
• Exercises
• Chapter 9 • Measurement in the Broader Research Context
• Before Scale Development
• Look for Existing Tools
• View the Construct in the Context of the Population of Interest
• Consider the Scale in the Context of Other Measures or Procedures
• After Scale Administration
• Analytic Issues
• Interpretation Issues
• Generalizability
• Final Thoughts
• Small Measurement and Big Measurement
• Canoes and Cruise Ships
• Measurement “Canoes” and Measurement “Cruise Ships”
• Practical Implications of Small Versus Big Measurement
• Remember, Measurement Matters
• Exercise
• References
• Index