Efnisyfirlit

• Half Title Page
• Series Page
• Title Page
• Copyright
• Dedication
• Series Editor’s Note
• Preface
• Contents
• Part I. Instrument Development and Analysis
  • 1. Introduction
    • Problems in Social Science Measurement
    • What is Measurement Theory?
    • Measurement Defined
      • The Nominal Level of Measurement
      • The Ordinal Level of Measurement
      • The Interval Level of Measurement
      • The Ratio Level of Measurement
      • Criticisms of Stevens’s Levels of Measurement
    • A Brief History of Testing
      • The Chinese Civil Service Examinations
      • Testing in Ancient Greece
      • Early European Testing
      • Testing in the United States
      • Testing in Business and Industry
      • Personality Assessment
    • Summary
    • Exercises
  • 2. Norms and Standardized Scores
    • Which to Use?
    • Norm Groups
      • Important Characteristics of the Norm Group: The “Three R’s”
    • Types of Norm-referenced Scores
      • Percentile Ranks
      • Standardized and Normalized Scores
      • Stanines
      • Normal Curve Equivalents
      • Developmental-Level Scores
    • Criterion-Referenced Testing
    • Summary
    • Exercises
  • 3. The Test Development Process
    • Steps in Scale Development
      • State the Purpose of the Scale
      • Identify and Define the Domain
      • Determine Whether a Measure Already Exists
      • Determine the Item Format
      • Write Out the Testing Objectives
      • Create the Initial Item Pool
      • Conduct the Initial Item Review
      • Conduct Preliminary Item Tryouts
      • Conduct a Large-Scale Field Test of Items
      • Prepare Guidelines for Administration
    • Summary
    • Exercises
  • 4. Writing Cognitive Items
    • Objective Item Types
      • Multiple-Choice Items
      • True–False Items
      • Matching Items
      • Short-Answer or Completion Items
    • Performance Assessments
      • Essay Questions
      • Performance Tasks
    • Summary
    • Exercises
  • 5. Writing Noncognitive Items
    • Noncognitive Item Types
      • Thurstone Scaling
      • Likert Scaling
      • Guttman Scaling
    • Theories of Item Responding
      • The Cognitive Process Model of Responding
      • Item Responses as Social Encounters
    • Problems in Measuring Noncognitive Outcomes
      • Response Distortion
      • Managing Response Distortion
    • Practical Issues in Noncognitive Scale Construction
      • Number of Scale Points
      • Labeling of Response Options
      • Inclusion of Negatively Oriented Items
      • Including a Neutral Option
    • Summary
    • Exercises
  • 6. Item Analysis for Cognitive and Noncognitive Items
    • Item Analysis for Cognitive Items
      • Item Difficulty
      • Item Discrimination
      • Evaluating the Distractors for Multiple-Choice Items
      • Corrections for Guessing
      • Summary of Analyses for Cognitive Items
    • Item Analysis for Noncognitive Items
      • Frequency Distributions and Descriptive Statistics
      • Interitem Correlations
      • Item–Total Correlations and Information from Reliability Analyses
      • Group Comparisons
      • Factor Analytic Methods
      • Summary of Analyses for Noncognitive Items
    • Use of Item Analysis Information
    • Exercises
• Part II. Reliability and Validity
  • 7. Introduction to Reliability and the Classical Test Theory Model
    • What Is Reliability?
    • Measurement Error and CTT
    • More on CTT
      • Properties of True and Error Scores in CTT
    • The CTT Definition of Reliability
    • Correlation between True and Observed Scores: The Reliability Index
    • Parallel, Tau-Equivalent, and Congeneric Measures
    • Reliability as the Correlation between Scores on Parallel Tests
    • Summary
    • Exercises
  • 8. Methods of Assessing Reliability
    • Internal Consistency
      • Reliability of a Composite
      • The Spearman–Brown Prophecy Formula and Split-Half Reliability
      • Coefficient Alpha
      • Other Internal Consistency Coefficients
      • Recommended Values for Internal Consistency Indices
      • Factors Affecting Internal Consistency Coefficient Values
      • Computational Examples for Coefficient Alpha
    • Test–Retest Reliability
      • Factors Affecting Coefficients of Stability
      • Recommended Values for Coefficients of Stability
    • Alternate Forms Reliability
      • Factors Affecting Coefficients of Equivalence
      • Recommended Values for Coefficients of Equivalence
    • Combining Alternate Forms and Test–Retest Reliability
      • Factors Affecting Coefficients of Equivalence and Stability
      • Recommended Values for Coefficients of Equivalence and Stability
    • The Standard Error of Measurement
      • Factors Affecting the SEM
      • Using the SEM to Place Confidence Intervals around Scores
      • Sample Dependence of Reliability Coefficients and the SEM
    • Reliability of Difference Scores
    • Summary
    • Exercises
  • 9. Interrater Agreement and Reliability
    • Measures of Interrater Agreement
      • Nominal Agreement
      • Cohen’s Kappa
    • Measures of Interrater Reliability
      • Coefficient Alpha
      • Intraclass Correlation
    • Summary
    • Exercises
  • 10. Generalizability Theory
    • Basic Concepts and Terminology
    • Facets, Objects of Measurement, and Universe Scores
      • Crossed and Nested Facets
      • Random and Fixed Facets
    • G Studies and D Studies
    • The G Theory Model
    • Computation of Variance Components
      • Computation of Variance Components for a One-Facet Design
      • Computation of Variance Components for a Two-Facet Design
      • Variance Components for Nested Designs
      • Variance Components for Designs with Fixed Facets
    • Decision Studies
      • Relative and Absolute Interpretations
      • Calculating the G and Phi Coefficients
      • Use of the D Study to Determine the Optimal Test Design
      • Decision Studies with Nested or Fixed Facets
    • Summary
    • Exercises
  • 11. Validity
    • Validity Defined
    • Traditional Forms of Validity Evidence: A Historical Perspective
      • Original Validity Types
      • Arguments against the “Tripartite” View of Validity
    • Current Conceptualizations of Validity
      • The Unified View of Validity
      • Focus on Interpretation and Use of Test Scores
      • Focus on Explanation and Cognitive Models
      • Inclusion of Values and Test Consequences in the Validity Framework
    • Obtaining Evidence of Validity
      • Introduction to the Argument-Based Approach to Validity
      • Types of Validity Evidence
    • Summary
    • Exercises
• Part III. Advanced Topics in Measurement Theory
  • 12. Exploratory Factor Analysis
    • The EFA–CFA Distinction
    • The EFA Model
      • The EFA Model: Diagrammatic Form
      • The EFA Model: Equation Form
    • Steps in Conducting EFA
      • Extracting the Factors
      • Determining the Number of Factors to Retain
      • Rotating the Factors
      • Interpreting the Factors
      • Data Requirements for EFA
      • Sample-Size Requirements
    • Summary
    • Exercises
  • 13. Confirmatory Factor Analysis
    • Differences between Exploratory and Confirmatory Factor Analyses
    • Advantages of CFA
    • CFA Model and Equations
    • Steps in Conducting a CFA
      • Model Specification
      • Model Identification
      • Estimation of Model Parameters
      • Model Testing
      • Respecification of the Model
    • Data Preparation and CFA Assumptions
      • Normality of Variable Distributions
      • Variable Scales
      • Outliers
      • Missing Data
      • Sampling Method
      • Sample Size
    • CFA-Based Reliability Estimation
      • Tests of Parameter Estimate Equivalence
      • Calculation of Coefficient Omega
    • Summary
    • Exercises
  • 14. Item Response Theory
    • Item Response Functions for IRT
    • IRT Models
      • The One-Parameter Logistic Model
      • The Two-Parameter Logistic Model
      • The Three-Parameter Logistic Model
      • IRT Models for Polytomous Items
    • Indeterminacy and Scaling
      • Scaling for the Rasch Model
      • Scaling for the 2PL and 3PL Models
    • Invariance of Parameter Estimates
    • Estimation
      • Maximum Likelihood Estimation
      • Bayesian Estimation Methods
    • Sample Size Requirements
    • Information, Standard Error of Measurement, and Reliability
      • Maximum Likelihood Estimation
      • EAP Estimation
    • IRT Assumptions
      • Correct Dimensionality
      • Local Independence
      • Functional Form
    • IRT Applications
      • Test Form Assembly
      • Equating
      • Computer Adaptive Testing Applications
      • Differential Item Functioning Applications
    • Summary
    • Exercises
  • 15. Diagnostic Classification Models
    • Categorical Latent Variables for DCMs
    • When to Use DCMs
    • Attribute Profiles
    • Diagnostic Classification Model: A Confirmatory Latent Class Model
    • The Latent Class Model
    • IRFs for DCMs
    • The Log-Linear Cognitive Diagnosis Model: A General DCM
      • Link Functions for DCMs
      • The Q-Matrix
      • IRF for Complex Structure Items
      • Fully Extending the IRF for the LCDM
      • Other General DCMs
    • Submodels of the LCDM
      • The Deterministic Inputs Noisy And Gate Model
      • The Compensatory Reparameterized Unified Model
      • The Deterministic Inputs Noisy Or Gate Model
      • Other Models
      • Which Model Should I Use?
    • Examinee Classifications
    • Summary
    • Exercises
  • 16. Bias, Fairness, and Legal Issues in Testing
    • Impact, Item and Test Bias, Differential Item Functioning, and Fairness Defined
    • Detecting Test and Item Bias
      • Test Bias
      • Item Bias
    • Choosing a DIF Detection Method
      • Purification of the Matching Variable
    • Interpretation of DIF and Test Bias
      • DIF as Construct-Irrelevant Variance
      • Sources of Test Bias
    • Test Fairness
      • Universal Design
      • Accommodations and Modifications
      • Need for More Research on DIF and Test Bias
      • Sensitivity Reviews
    • Legal Issues in Testing
      • Legislation under Which Tests Can Be Challenged
      • Court Cases Relevant to Testing
    • Summary
    • Exercises
  • 17. Standard Setting
    • Common Elements of Standard-Setting Procedures
      • Step 1: Select a Standard-Setting Procedure
      • Step 2: Choose the Panelists
      • Step 3: Prepare Descriptions of Each Performance Category
      • Step 4: Train the Panelists to Use the Chosen Procedure
      • Step 5: Collect Panelists’ Judgments
      • Step 6: Provide Panelists with Feedback and Discuss
      • Step 7: Collect a Second Set of Judgments and Create Recommended Cut Scores
      • Step 8: Conduct an Evaluation of the Standard-Setting Process
      • Step 9: Compile a Technical Report, Including Validity Evidence
    • Standard-Setting Procedures
      • The Angoff Method
      • The Bookmark Procedure
      • The Contrasting Groups Method
      • The Borderline Group Method
      • The Body of Work Method
    • Validity Evidence for Standard Setting
      • Procedural Evidence
      • Internal Evidence
      • External Evidence
    • Summary
    • Exercises
  • 18. Test Equating
    • Equating Defined
      • Alternatives to Equating
    • Equating Designs
      • Single-Group Design
      • Random-Groups Design
      • Common Item Nonequivalent Groups Design
    • Methods of Equating
      • Mean Equating
      • Linear Equating
      • Equipercentile Equating
      • IRT Equating Methods
    • Practical Considerations in Equating
      • Guidelines for Choosing Common Items
      • Error in Equating
      • Sample-Size Requirements
      • Systematic Equating Error
      • Choice of Equating Method
    • Summary
    • Exercises
• Answers to Exercises
• References
• Author Index
• Subject Index
• About the Author

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