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Scale Development
A practical and theoretically grounded guide to creating, evaluating, and validating multi-item measurement instruments—scales and indices—for assessing unobservable social and psychological constructs.
A profile of this book is on the way.
What it’s about
Scale Development: Theory and Applications demystifies psychometrics for researchers who are not measurement specialists but who must quantify intangible constructs—beliefs, attitudes, motivations, perceptions—to answer their substantive questions. DeVellis and Thorpe combine accessible explanations of classical measurement theory, reliability, validity, factor analysis, and item response theory with a step-by-step practical roadmap for generating items, choosing formats, reviewing content, administering to a development sample, and optimizing scale length. The fifth edition adds a major treatment of indices (formative measures) as distinct from scales (reflective measures), clarifying a widely misunderstood distinction and the different methodologies each requires. Throughout, the authors stress that careful measurement is not a secondary technicality but a load-bearing foundation of valid research: poor measurement imposes an absolute ceiling on the conclusions a study can support. The book balances conceptual clarity, real-world examples, and recent methodological developments to equip readers to build better tools, choose existing ones wisely, and use them appropriately.
The through-line
- Who it’s for
- A behavioral, social, or health science researcher who needs to quantify an intangible construct and wants a reliable, valid measurement instrument to answer their substantive research question.
- The problem
- No suitable off-the-shelf measurement scale exists for the construct of interest, or existing tools are of questionable suitability. The researcher feels uneasy and unfamiliar with proper measurement methods, worried that made-up items will be unreliable or invalid and that they don't really know what they are measuring.
- The plan
- Determine clearly what you want to measure, grounded in theory.
- Generate a large pool of candidate items reflecting the construct.
- Determine the appropriate response format for measurement.
- Have the initial item pool reviewed by content experts.
- Conduct cognitive interviewing with potential respondents.
- The payoff
- The researcher possesses a reliable, valid, and usable instrument optimally suited to their research question. · Measurement can be taken more or less for granted thereafter, freeing attention for substantive issues. · Conclusions drawn from the research are trustworthy because the proxy genuinely reflects the intended construct.
See our guide
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Additional reading
- Causal Inferences in Nonexperimental Research · Blalock, H. M. Jr. (1964)
Cited as a foundational text for causal modeling, which is the basis for the structural equation models used throughout the book to analyze measurement quality and correct for error.
- Convergent and discriminant validation by the multitrait-multimethod matrices · Campbell, D. T., & Fiske, D. W. (1959)
The seminal paper that introduced the Multitrait-Multimethod (MTMM) matrix, which is the core experimental design for evaluating question quality in this book.
- Questions and Answers in Attitude Survey: Experiments on Question Form, Wording and Context · Schuman, H., & Presser, S. (1981)
The classic text on experimental survey methodology, frequently cited for its split-ballot experiments demonstrating the powerful effects of question wording and format on responses.
- Mail and Internet Surveys. The Tailored Design Method · Dillman, D. A. (2000)
Referenced as the key source for practical guidance on questionnaire layout, ordering, and administration across different survey modes, topics which the book touches on but does not cover in depth.
- Structural Equations with Latent Variables · Bollen, K. A. (1989)
Cited as a comprehensive textbook for Structural Equation Modeling (SEM), the advanced statistical technique required to implement the MTMM models and error-correction procedures central to the book's methodology.
- The Psychology of Survey Response · Tourangeau, R., Rips, L. J., & Rasinski, K. (2000)
Frequently referenced for its comprehensive model of the cognitive processes underlying survey responses (comprehension, retrieval, judgment, and reporting), which provides the theoretical explanation for why question characteristics affect data quality.
- Survey Sampling · Kish, L. (1965)
The book frequently refers to this text, recommending it as a primary resource for its comprehensive discussions of sampling practice.
- Sampling Techniques · Cochran, W. G. (1977)
Recommended by the author as a key text for its thorough treatment of the statistical theory underlying survey sampling.
- Sample Survey Methods and Theory · Hansen, M. H., Hurwitz, W. N., and Madow, W. G. (1953)
Cited as a foundational text for its discussion of the practical application of sampling methods.
- Survey Methods in Social Investigation · Moser, C. A. and Kalton, G. (1971)
Co-authored by the book's author, it provides a broader introduction to survey methods, placing sampling in context.