Psychometrics An Introduction

ISBN-10: 1452256802

ISBN-13: 9781452256801

Edition: 2nd 2014

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Description:

In Psychometrics, R Michael Furr and Verne R Bacharach centre their presentation of material around a conceptual understanding of psychometric issues, such as validity and reliability, and on purpose rather than procedure, the 'why' rather than the 'how to'. By emphasizing concepts over mathematical proofs and by focusing on practical significance, this book will assist students in appreciating not just how measurement problems can be addressed but why it is important to address them. The Second Edition has been thoroughly revised to improve the clarity and accessibility of key concepts and to increase the depth of discussions. Many new tables and figures have been added and the references have been significanly updated and expanded. An entirely new chapter on confirmatory factor analysis has also been added to this edition. This new chapter focuses on the use of CFA to evaluate measurement models, including in-depth discussion of the logic and interpretation of the process. Key features of this volume: - presents information in a clear, easy-to-read, conversational style: the authors introduce concepts in a way that is accessible to non-professionals without sacrificing the academic integrity of the material - highlights practical applications: intended to enhance readers' appreciation of the importance of psychometrics, the book provides examples that will resonate with students - offers an up-to-date treatment of topics in psychometrics: the book offers readers the most contemporary views of topics in psychometrics available in the non-technical psychometric literature - introduces statistical procedures in the context of their use rather than in a separate chapter: the authors integrate statistics with a discussion of their use as tools to solve particular psychometric problems, encouraging a more complete understanding of both.
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Book details

Edition: 2nd
Copyright year: 2014
Publisher: SAGE Publications, Incorporated
Publication date: 2/27/2013
Binding: Hardcover
Pages: 472
Size: 7.00" wide x 10.00" long x 1.00" tall
Weight: 2.090

Verne R. Bacharach is professor of psychology at Appalachian State University. He has held faculty appointments at the University of Alabama, Peabody College of Vanderbilt University, and Acadia University in Nova Scotia and has chaired the departments at Appalachian State and Acadia. He has taught undergraduate and graduate courses in statistics, tests and measurements, and research methods for nearly 40 years. He has a long journal publication history of research and review articles. Dr. Bacharach obtained a Ph.D. in experimental psychology from the University of Kansas in 1971.

R. Michael Furr is Professor of Psychology and McCulloch Faculty Fellow at Wake Forest University, where he received the 2012 Award for Excellence in Research. His methodological work focuses on the measurement of similarity between psychological profiles, on the measurement of behavior, and on contrast analysis. His substantive research focuses on personality judgment and on the links between personality, situational forces, and behavior. He is a former associate editor of the Journal of Research in Personality , a former executive editor of the Journal of Social Psychology , and a consulting editor for several other scholarly journals. He has taught graduate and undergraduate courses in psychometrics, psychological testing, personality psychology, statistics, and research methods at Appalachian State University and Wake Forest University.

Preface
The Conceptual Orientation of This Book, Its Purpose, and the Intended Audience
Organizational Overview
Acknowledgments
About the Authors
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
Psychometrics
What Is Psychometrics?
Francis Galton and the Scope of Psychometrics
Challenges to Measurement in Psychology
Theme: The Importance of Individual Differences
Suggested Readings
Basic Concepts in Measurement
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
Summary
Suggested Readings
Individual Differences and Correlations
The Nature of Variability
Importance of Individual Differences
Variability and Distributions of Scores
Central Tendency
Variability
Distribution Shapes and Normal Distributions
Quantifying the Association Between Distributions
Interpreting the Association Between Two Variables
Covariance
Correlation
Variance and Covariance for "Composite Variables"
Binary Items
Interpreting Test Scores
z Scores (Standard Scores)
Converted Standard Scores (Standardized Scores)
Percentile Ranks
Normalized Scores
Test Norms
Representativeness of the Reference Sample
Summary
Suggested Readings
Test Dimensionality and Factor Analysis
Test Dimensionality
Three Dimensionality Questions
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 Quick Look at Confirmatory Factor Analysis
Summary
Suggested Readings
Reliability
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
Lack of Error Variance
The (Squared) Correlation Between Observed Scores and True Scores
Lack of (Squared) Correlation Between Observed Scores and Error Scores
Reliability and the Standard Error of Measurement
Parallel Tests
Domain Sampling Theory
Summary
Suggested Readings
Empirical Estimates of Reliability
Alternate Forms Reliability
Test-Retest Reliability
Internal Consistency Reliability
Split-Half Estimates of Reliability
"Raw" Coefficient Alpha
"Standardized" Coefficient Alpha
Raw Alpha for Binary Items: KR<sub>20</sub>
Accuracy and Use of Internal Consistency Estimates of Reliability: Theory and Reality
Internal Consistency Versus Dimensionality
Factors Affecting the Reliability of Test Scores
Sample Homogeneity and Reliability Generalization
Reliability of 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
Summary
Note
Suggested Readings
The Importance of Reliability
Applied Behavioral Practice: Evaluation of an Individual's Test Score
Point Estimates of True Scores
True Score Confidence Intervals
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
Test Construction and Refinement
Item Discrimination and Other Information Regarding Internal Consistency
Item Difficulty (Mean) and Item Variance
Summary
Suggested Readings
VALIDITY
Validity: Conceptual Basis
What Is Validity?
The Importance of Validity
Validity Evidence: Test Content
Threats to Content Validity
Content Validity Versus Face Validity
Validity Evidence: Internal Structure of the Test
Validity Evidence: Response Processes
Validity Evidence: Associations With Other Variables
Validity Evidence: Consequences of Testing
Other Perspectives on Validity
Contrasting Reliability and Validity
Summary
Suggested Readings
Estimating and Evaluating Convergent and Discriminant Validity Evidence
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
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
Summary
Notes
Suggested Readings
Threats to Psychometric Quality
Response Biases
Types of Response Biases
Acquiescence Bias ("Yea-Saying and Nay-Saying")
Extreme and Moderate Responding
Social Desirability
Malingering
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
Test Bias
Why Worry About Test Score Bias?
Detecting Construct Bias: Internal Evaluation of a Test
Item Discrimination Index
Factor Analysis
Differential Item Functioning Analyses
Rank Order
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
Outcome 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
Summary
Suggested Readings
Advanced Psychometric Approaches
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 Example
Preliminary Steps
Specification of Measurement Model
Computations
Interpreting and Reporting Output
Model Modification and Reanalysis (If Necessary)
Comparing Models
Summary
CFA and Reliability
CFA and Validity
Summary
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
G Study
D Study
Conducting and Interpreting Generalizability Theory Analysis: A Two-Facet Design
G Study
D Study
Other Measurement Designs
Number of Facets
Random Versus Fixed Facets
Crossed Versus Nested Designs
Relative Versus Absolute Decisions
Summary
Suggested Readings
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
Graded Response Model
Obtaining Parameter Estimates: A IPL Example
Item and Test Information
Item Characteristic Curves
Item Information and Test Information
Applications of IRT
Test Development and Improvement
Differential Item Functioning
Person Fit
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