Description
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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
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