Effective measurement is a cornerstone of scientific research. Yet many social science researchers lack the tools to develop appropriate assessment instruments for the measurement of latent social-psychological constructs.
Scaling Procedures: Issues and Applications examines the issues involved in developing and validating multi-item self-report scales of latent constructs. Distinguished researchers and award-winning educators Richard G. Netemeyer, William O. Bearden, and Subhash Sharma present a four-step approach for multi-indicator scale development. With these steps, the authors include relevant empirical examples and a review of the concepts of dimensionality, reliability, and validity.
Interdisciplinary in application, this reader-friendly handbook includes
- A discussion of measurement in the social sciences and the importance of theory in scale development
- Techniques for assessing dimensionality of constructs
- An overview of reliability and validity models, theory, and criteria
- Suggestions for generating and judging measurement items
- Recommended procedures for designing and conducting studies to develop the scale
- Confirmatory Factor Analyses (CFA) for finalizing the scale
Scaling Procedures: Issues and Applications supplies cutting-edge strategies for developing and refining measures. Providing concise chapter introductions and summaries, as well as numerous tables, figures, and exhibits, the authors present recommended steps and overlapping activities in a logical, sequential progression.
Designed for graduate students in measurement/psychometrics, structural equation modeling, and survey research seminars across the social science disciplines, Scaling Procedures: Issues and Applications also addresses the needs of researchers and academics in all business, psychology, and sociology-related disciplines.
Tabla de materias
About the Authors
Chapter One: Introduction and Overview
Purpose of the Book.
Perspectives on Measurement in the Social Sciences.
Latent Constructs
Overview of dimensionality, reliability, and validity
Overview of recommended procedures and steps in scale development.
Chapter Two: Dimensionality
Introduction.
Dimensionality of construct, items, and a set of items.
Does uni-dimensionality of a set of items imply uni-dimensionality of items or construct?
Relevance of uni-dimensionality.
How to assess dimensionality of constructs.
Chapter Three: Reliability
Introduction
The true-score model
Coefficient alpha
Generalizability Theory
Chapter Four: Validity
Overview of Construct Validity
Translation validity
Criterion validity
Convergent and discriminant validity
Known-group validity
Nomological validity
Chapter Five: Steps 1 and 2: Construct Definition and Generating and Judging Measurement items Chapter 5: Steps 1 and 2: Construct Definition and Judging Measurement Items
Introduction
Step 1: Construct definition and content domain
Step 2: Generating and judging measurement items
Applications of Steps 1 and 2.
Chapter Six: Step 3: Designing and Conducting Studies to Develop the Scale
Introduction
Pilot testing
Conducting multiple studies for initial development and validation
Initial item analyses: Exploratory factor analysis (EFA)
Initial item and reliability analyses
A final caveat
EFA and item and reliability analyses examples from the literature
Chapter 7: Step 4: Finalizing the Scale
Introduction
EFA and additional item analyses
Confirmatory Factor Analyses (CFA)
Additional evaluations of validity
Establishing norms
Applying generalizability theory
Chapter Eight: Concluding Remarks
Index
Sobre el autor
Dr. Subhash Sharma is James F. Kane Professor of Marketing, Marketing Department, Darla Moore School of Business, the University of South Carolina. Professor Sharma′s research interests include Marketing strategy, structural equation modeling, data mining, customer relationship management, marketing-operations interface, and global marketing strategies.
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