Scale Development And Score Validation

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In the Fourth Edition of Scale Development, Robert F. DeVellis demystifies measurement by emphasizing a logical rather than strictly mathematical understanding of concepts. The text supports readers in comprehending newer approaches to measurement, comparing them to classical approaches, and grasping more clearly the relative merits of each. This edition addresses new topics pertinent to modern measurement approaches and includes additional exercises and topics for class discussion. Available with Perusall—an eBook that makes it easier to prepare for class Perusall is an award-winning eBook platform featuring social annotation tools that allow students and instructors to collaboratively mark up and discuss their SAGE textbook. Backed by research and supported by technological innovations developed at Harvard University, this process of learning through collaborative annotation keeps your students engaged and makes teaching easier and more effective. Learn more.

Clinicians and those in health sciences are frequently called upon to measure subjective states such as attitudes, feelings, quality of life, educational achievement and aptitude, and learning style in their patients. This fourth edition of Health Measurement Scales enables these groups, who often have limited knowledge of statistics, to both develop scales to measure non-tangible health outcomes, and better evaluate and differentiate between existing tools. It covers how the individual items are developed; various biases that can affect responses (eg social desirability, yea-saying, framing); various response options; how to select the best items in the set; how to combine them into a scale; and then how to determine the reliability and validity of the scale. It concludes with a discussion of ethical issues that may be encountered, and guidelines for reporting the results of the scale development process. Appendices include a comprehensive guide to finding existing scales, and a brief introduction to exploratory and confirmatory factor analysis. It synthesizes the theory of scale construction with practical advice, making it the ultimate guide to how to develop and validate measurement scales that are to be used in the health sciences.

“Dr. Dimitrov has constructed a masterpiece—a classic resource that should adorn the shelf of every counseling researcher and graduate student serious about the construction and validation of high quality research instruments. —Bradley T. Erford, PhD Loyola University Maryland Past President, American Counseling Association “This book offers a comprehensive treatment of the statistical models and methods needed to properly examine the psychometric properties of assessment scale data. It is certain to become a definitive reference for both novice and experienced researchers alike.” —George A. Marcoulides, PhD University of California, Riverside This instructive book presents statistical methods and procedures for the validation of assessment scale data used in counseling, psychology, education, and related fields. In Part I, measurement scales, reliability, and the unified construct-based model of validity are discussed, along with key steps in instrument development. Part II describes factor analyses in construct validation, including exploratory factor analysis, confirmatory factor analysis, and models of multitrait-multimethod data analysis. Traditional and Rasch-based analyses of binary and rating scales are examined in Part III. Dr. Dimitrov offers students, researchers, and clinicians step-by-step guidance on contemporary methodological principles, statistical methods, and psychometric procedures that are useful in the development or validation of assessment scale data. Numerous examples, tables, and figures provided throughout the text illustrate the underlying principles of measurement in a clear and concise manner for practical application. *Requests for digital versions from ACA can be found on www.wiley.com. *To purchase print copies, please visit the ACA website here. *Reproduction requests for material from books published by ACA should be directed to [email protected].

A new edition of this practical guide for clinicians who are developing tools to measure subjective states, attitudes, or non-tangible outcomes in their patients, suitable for those who have no knowledge of statistics.

Providing a comprehensive foundation for planning, executing, and monitoring public health research of all types, this book goes beyond traditional epidemiologic research designs to cover technology-based approaches emerging in the new public health landscape.

Carol A. Chapelle shows readers how to design validation research for tests of human capacities and performance. Any test that is used to make decisions about people or programs should have undergone extensive research to demonstrate that the scores are actually appropriate for their intended purpose. Argument-Based Validation in Testing and Assessment is intended to help close the gap between theory and practice, by introducing, explaining, and demonstrating how test developers can formulate the overall design for their validation research from an argument-based perspective.