Scaling Procedures: Issues and Applications
Year: 2003
Type: article
Abstract: 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. \n \nScaling 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. \n \nInterdisciplinary in application, this reader-friendly handbook includes \n \nA discussion of measurement in the social sciences and the importance of theory in scale development \nTechniques for assessing dimensionality of constructs \nAn overview of reliability and validity models, theory, and criteria \nSuggestions for generating and judging measurement items \nRecommended procedures for designing and conducting studies to develop the scale \nConfirmatory Factor Analyses (CFA) for finalizing the scale \n \nScaling 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. \n \nDesigned 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. \n \n<출처: Sage, \nhttps://us.sagepub.com/en-us/nam/scaling-procedures/book10174#description>
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W579060270