Measurement Theory and Applications for the Social Sciences

Höfundur Deborah L. Bandalos

Útgefandi Guilford Publications, Inc.

Snið Page Fidelity

Print ISBN 9781462532131

Útgáfa 0

Útgáfuár 2018

6.690 kr.

Description

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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