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• Preface
• The Conceptual Orientation of This Book, Its Purpose, and the Intended Audience
• Organizational Overview
• New to This Edition
• General Changes
• Chapter-Specific Changes
• Author’s Acknowledgments
• Publisher’s Acknowledgments
• About the Author
• Chapter 1 • Psychometrics and the Importance of Psychological Measurement
• Why Psychological Testing Matters to You
• Observable Behavior and Unobservable Psychological Attributes
• Psychological Tests: Definition and Types
• What Is a Psychological Test?
• Types of Tests
• What Is Psychometrics?
• Psychometrics
• A Brief History of Psychometrics
• Challenges to Measurement in Psychology
• The Importance of Individual Differences
• But Psychometrics Goes Well Beyond “Differential” Psychology
• Suggested Readings
• PART I • BASIC CONCEPTS IN MEASUREMENT
• Chapter 2 • Scaling
• Fundamental Issues With Numbers
• The Property of Identity
• The Property of Order
• The Property of Quantity
• The Number 0
• Units of Measurement
• Additivity and Counting
• Additivity
• Counts: When Do They Qualify as Measurement?
• Four Scales of Measurement
• Nominal Scales
• Ordinal Scales
• Interval Scales
• Ratio Scales
• Scales of Measurement: Practical Implications
• Additional Issues Regarding Scales of Measurement
• Technical Appendix: R Syntax
• Summary
• Suggested Readings
• Chapter 3 • Differences, Consistency, and the Meaning of Test Scores
• The Nature of Variability
• Importance of Individual Differences
• Variability and Distributions of Scores
• Central Tendency
• Variability
• Distribution Shapes and Normal Distributions
• Quantifying the Association or Consistency Between Distributions
• Interpreting the Association Between Two Variables
• Scatterplots: Visually Representing the Association Between Two Variables
• Covariance
• Correlation
• Variance and Covariance for “Composite Variables”
• Binary Items
• Interpreting Test Scores
• Needed: An Interpretive Frame of Reference
• z Scores (Standard Scores)
• Converted Standard Scores (Standardized Scores)
• Percentile Ranks
• Normalized Scores
• Test Norms
• Representativeness of the Reference Sample
• Technical Appendix: R Syntax
• Summary
• Suggested Readings
• Chapter 4 • Test Dimensionality and Factor Analysis
• Test Dimensionality
• Three Dimensionality Questions: What They Are and Why They Matter
• Unidimensional Tests
• Multidimensional Tests With Correlated Dimensions (Tests With Higher-Order Factors)
• Multidimensional Tests With Uncorrelated Dimensions
• The Psychological Meaning of Test Dimensions
• Factor Analysis: Examining the Dimensionality of a Test
• The Logic and Purpose of Exploratory Factor Analysis: A Conceptual Overview
• Conducting and Interpreting an Exploratory Factor Analysis
• A Deeper Perspective on Factors, Factor Loadings, and Rotation
• Factor Analysis of Binary Items
• A Quick Look at Confirmatory Factor Analysis
• Technical Appendix: R Syntax
• Summary
• Suggested Readings
• PART II • RELIABILITY
• Chapter 5 • Reliability: Conceptual Basis
• Overview of Reliability and Classical Test Theory
• Observed Scores, True Scores, and Measurement Error
• Variances in Observed Scores, True Scores, and Error Scores
• Four Ways to Think of Reliability
• Reliability as the Ratio of True Score Variance to Observed Score Variance
• Reliability as Lack of Error Variance
• Reliability as the (Squared) Correlation Between Observed Scores and True Scores
• Reliability as the Lack of (Squared) Correlation Between Observed Scores and Error Scores
• Reliability and the Standard Error of Measurement
• From Theory to Practice: Measurement Models and Their Implications for Estimating Reliability
• Overview of Key Assumptions
• Parallel Tests
• Tau-Equivalent and Essentially Tau-Equivalent Tests
• Congeneric Tests
• Tests With Correlated Errors
• Summary
• Domain Sampling Theory
• Summary
• Suggested Readings
• Chapter 6 • Empirical Estimates of Reliability
• Alternate Forms Method of Estimating Reliability
• Test–Retest Method of Estimating Reliability
• Internal Consistency Method of Estimating Reliability
• Split-Half Estimates of Reliability
• “Raw” Coefficient Alpha
• “Standardized” Coefficient Alpha
• Raw Alpha for Binary Items: KR20
• Omega
• On the Assumptions Underlying Alpha and Omega, the Relative Applicability of Those Indices, and Their Limitations
• Internal Consistency Versus Dimensionality
• Factors Affecting the Reliability of Test Scores
• Sample Heterogeneity and Reliability Generalization
• Reliability of Difference Scores
• Defining Difference Scores
• Estimating the Reliability of Difference Scores
• Factors Affecting the Reliability of Difference Scores
• The Problem of Unequal Variability
• Difference Scores: Summary and Caution
• Technical Appendix: R Syntax
• Summary
• Suggested Readings
• Note
• Chapter 7 • The Importance of Reliability
• Applied Behavioral Practice: Evaluation of an Individual’s Test Score
• Point Estimates of True Scores
• Confidence Intervals
• Debate and Alternatives
• Summary
• Behavioral Research
• Reliability, True Associations, and Observed Associations
• Measurement Error (Low Reliability) Attenuates the Observed Associations Between Measures
• Reliability, Effect Sizes, and Statistical Significance
• Implications for Conducting and Interpreting Behavioral Research
• Summary
• Test Construction and Refinement
• Item Discrimination and Other Information Regarding Internal Consistency
• Item Difficulty (Mean) and Item Variance
• Technical Appendix: R Syntax
• Summary
• Suggested Readings
• PART III • VALIDITY
• Chapter 8 • Validity: Conceptual Basis
• What Is Validity?
• The Importance of Validity
• Validity Evidence: Test Content
• Expert Rating Evidence
• Threats to Content Validity
• Content Validity Versus Face Validity
• Validity Evidence: Internal Structure of the Test
• Factor-Analytic Evidence
• Validity Evidence: Response Processes
• Direct Evidence
• Indirect Evidence
• Validity Evidence: Associations With Other Variables
• Convergent Evidence
• Discriminant Evidence
• Criterion, Concurrent, and Predictive Evidence
• Validity Evidence: Consequences of Testing
• Evidence of Intended Effects
• Evidence Regarding Unintended Differential Impact on Groups
• Evidence Regarding Unintended Systemic Effects
• Other Perspectives on Validity
• Contrasting Reliability and Validity
• Summary
• Suggested Readings
• Chapter 9 • Estimating and Evaluating Convergent and Discriminant Validity Evidence
• A Construct’s Nomological Network
• Methods for Evaluating Convergent and Discriminant Validity
• Focused Associations
• Sets of Correlations
• Multitrait–Multimethod Matrices
• Quantifying Construct Validity
• Factors Affecting a Validity Coefficient
• Associations Between Constructs
• Random Measurement Error and Reliability
• Restricted Range
• Skew and Relative Proportions
• Method Variance
• Time
• Predictions of Single Events
• Interpreting a Validity Coefficient
• Squared Correlations and “Variance Explained”
• Estimating Practical Effects: Binomial Effect Size Display, Taylor-Russell Tables, Utility Analysis, and Sensitivity/Specificity
• Guidelines or Norms for a Field
• Statistical Significance
• Technical Appendix: R Syntax
• Summary
• Suggested Readings
• Notes
• PART IV • THREATS TO PSYCHOMETRIC QUALITY
• Chapter 10 • Response Biases
• Types of Response Biases
• Acquiescence Bias (“Yea-Saying and Nay-Saying”)
• Extreme and Moderate Responding
• Social Desirability (“Faking Good”)
• Malingering (“Faking Bad”)
• Careless or Random Responding
• Guessing
• Methods for Coping With Response Biases
• Minimizing the Existence of Bias by Managing the Testing Context
• Minimizing the Existence of Bias by Managing Test Content
• Minimizing the Effects of Bias by Managing Test Content or Scoring
• Managing Test Content to Detect Bias and Intervene
• Using Specialized Tests to Detect Bias and Intervene
• Response Biases, Response Sets, and Response Styles
• Summary
• Suggested Readings
• Chapter 11 • Test Bias
• Why Worry About Test Score Bias?
• Detecting Construct Bias: Internal Evaluation of a Test
• Reliability
• Rank Order
• Item Discrimination Index
• Factor Analysis
• Differential Item Functioning Analyses
• Summary
• Detecting Predictive Bias: External Evaluation of a Test
• Basics of Regression Analysis
• One Size Fits All: The Common Regression Equation
• Intercept Bias
• Slope Bias
• Intercept and Slope Bias
• Criterion Score Bias
• The Effect of Reliability
• Other Statistical Procedures
• Test Fairness
• Example: Is the SAT Biased in Terms of Race or Socioeconomic Status?
• Race/Ethnicity
• Socioeconomic Status
• Technical Appendix: R Syntax
• Summary
• Suggested Readings
• Notes
• PART V • ADVANCED PSYCHOMETRIC APPROACHES
• Chapter 12 • Confirmatory Factor Analysis
• On the Use of EFA and CFA
• The Frequency and Roles of EFA and CFA
• Using CFA to Evaluate Measurement Models
• The Process of CFA for Analysis of a Scale’s Internal Structure
• Overview of CFA and an Example
• Preliminary Steps
• Step 1: Specification of the Measurement Model
• Step 2: Computations
• Step 3: Interpreting and Reporting Output
• Step 4: Model Modification and Reanalysis (If Necessary)
• Comparing Models
• Summary
• CFA and Reliability
• Evaluating Types of Classical Test Theory Measurement Models
• Estimating Reliability (Omega Index)
• CFA and Validity
• CFA and Measurement Invariance
• The Meaning of Measurement Invariance
• Levels of Invariance: Meaning and Detection
• Technical Appendix: R Syntax
• Summary
• Suggested Readings
• Chapter 13 • Generalizability Theory
• Multiple Facets of Measurement
• Generalizability, Universes, and Variance Components
• G Studies and D Studies
• Conducting and Interpreting Generalizability Theory Analysis: A One-Facet Design
• Phase 1: G Study
• Phase 2: D Study
• Conducting and Interpreting Generalizability Theory Analysis: A Two-Facet Design
• Phase 1: G Study
• Phase 2: D Study
• Other Measurement Designs
• Number of Facets
• Random Versus Fixed Facets
• Crossed Versus Nested Designs
• Relative Versus Absolute Decisions
• A Practical, Consistency-Oriented Interpretation of Variance Components
• Systematic Variance Components Reflect “Consistent Variance”
• Residual/Error Variance Component Reflects Inconsistent Variance
• Generalizability Coefficients as the Proportion of Variance That Is Consistent
• More Complex Designs
• Technical Appendix: R Syntax
• Summary
• Suggested Readings
• Notes
• Chapter 14 • Item Response Theory and Rasch Models
• Factors Affecting Responses to Test Items
• Respondent Trait Level as a Determinant of Item Responses
• Item Difficulty as a Determinant of Item Responses
• Item Discrimination as a Determinant of Item Responses
• Guessing
• IRT Measurement Models
• One-Parameter Logistic Model (or Rasch Model)
• Two-Parameter Logistic Model
• Three-Parameter Logistic Model
• Graded Response Model
• Obtaining Parameter Estimates: A 1PL Example
• Model Fit
• Item and Test Information
• Item Characteristic Curves
• Item Information and Test Information
• Applications of IRT
• Test Development and Improvement
• Differential Item Functioning
• Person Fit
• Computerized Adaptive Testing
• Technical Appendix: R Syntax
• Summary
• Suggested Readings
• Glossary
• References
• Index