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This book proposes a conceptual framework for understanding measurement across a broad range of scientific fields and areas of application, such as physics, engineering, education, and psychology. The authors, who themselves span these disciplines, argue that the justification of the public trust attributed to measurement results can in principle apply identically to both physical and psychosocial properties. They further argue that the lack of a common conceptualization of measurement hampers interdisciplinary communication and limits the ability to share knowledge. They advance their views by first surveying the conceptual history of the philosophy of measurement and arguing that classical, operationalist and representational perspectives on measurement each make important contributions but also each have important shortcomings. A synthesis is then offered as the foundation for a new conceptual framework. The authors describe how the framework, which operates as a shared concept system, supports understanding measurement’s work in different domains, using examples in the physical and human sciences. They consider connections and consequences with respect to causality, objectivity, and intersubjectivity, among other topics, and how measurement science concepts and issues are construed across these disciplines and settings. They also address contemporary issues and controversies within measurement in the light of the framework, including operationalism, definitional uncertainty, and the relations between measurement and computation. The book concludes with a justification for the basic claim that measurement is an empirical and informational process that produces explicitly justifiable information. Researchers and academics across a wide range of disciplines including biological, physical, social and behavioral scientists, as well as specialists in measurement and philosophy will appreciate the work’s fresh and provocative approach to the field at a time when sound measurements of complex scientific systems are increasingly essential to solving critical global problems.
This book proposes a conceptual framework for understanding measurement across a broad range of scientific fields and areas of application, such as physics, engineering, education, and psychology. The authors, who themselves span these disciplines, argue that the justification of the public trust attributed to measurement results can in principle apply identically to both physical and psychosocial properties. They further argue that the lack of a common conceptualization of measurement hampers interdisciplinary communication and limits the ability to share knowledge. They advance their views by first surveying the conceptual history of the philosophy of measurement and arguing that classical, operationalist and representational perspectives on measurement each make important contributions but also each have important shortcomings. A synthesis is then offered as the foundation for a new conceptual framework. The authors describe how the framework, which operates as a shared concept system, supports understanding measurement’s work in different domains, using examples in the physical and human sciences. They consider connections and consequences with respect to causality, objectivity, and intersubjectivity, among other topics, and how measurement science concepts and issues are construed across these disciplines and settings. They also address contemporary issues and controversies within measurement in the light of the framework, including operationalism, definitional uncertainty, and the relations between measurement and computation. The book concludes with a justification for the basic claim that measurement is an empirical and informational process that produces explicitly justifiable information. Researchers and academics across a wide range of disciplines including biological, physical, social and behavioral scientists, as well as specialists in measurement and philosophy will appreciate the work’s fresh and provocative approach to the field at a time when sound measurements of complex scientific systems are increasingly essential to solving critical global problems.
Which types of validity evidence should be considered when determining whether a scale is appropriate for a given measurement situation? What about reliability evidence? Using clear explanations illustrated by examples from across the social and behavioral sciences, this engaging text prepares students to make effective decisions about the selection, administration, scoring, interpretation, and development of measurement instruments. Coverage includes the essential measurement topics of scale development, item writing and analysis, and reliability and validity, as well as more advanced topics such as exploratory and confirmatory factor analysis, item response theory, diagnostic classification models, test bias and fairness, standard setting, and equating. End-of-chapter exercises (with answers) emphasize both computations and conceptual understanding to encourage readers to think critically about the material. ÿ
Historical and Conceptual Foundations of Measurement in the Human Sciences explores the assessment and measurement of nonphysical attributes that define human beings: abilities, personalities, attitudes, dispositions, and values. The proposition that human attributes are measurable remains controversial, as do the ideas and innovations of the six historical figures—Gustav Fechner, Francis Galton, Alfred Binet, Charles Spearman, Louis Thurstone, and S. S. Stevens—at the heart of this book. Across 10 rich, elaborative chapters, readers are introduced to the origins of educational and psychological scaling, mental testing, classical test theory, factor analysis, and diagnostic classification and to controversies spanning the quantity objection, the role of measurement in promoting eugenics, theories of intelligence, the measurement of attitudes, and beyond. Graduate students, researchers, and professionals in educational measurement and psychometrics will emerge with a deeper appreciation for both the challenges and the affordances of measurement in quantitative research.
One of the pathways by which the scientific community confirms the validity of a new scientific discovery is by repeating the research that produced it. When a scientific effort fails to independently confirm the computations or results of a previous study, some fear that it may be a symptom of a lack of rigor in science, while others argue that such an observed inconsistency can be an important precursor to new discovery. Concerns about reproducibility and replicability have been expressed in both scientific and popular media. As these concerns came to light, Congress requested that the National Academies of Sciences, Engineering, and Medicine conduct a study to assess the extent of issues related to reproducibility and replicability and to offer recommendations for improving rigor and transparency in scientific research. Reproducibility and Replicability in Science defines reproducibility and replicability and examines the factors that may lead to non-reproducibility and non-replicability in research. Unlike the typical expectation of reproducibility between two computations, expectations about replicability are more nuanced, and in some cases a lack of replicability can aid the process of scientific discovery. This report provides recommendations to researchers, academic institutions, journals, and funders on steps they can take to improve reproducibility and replicability in science.
A comprehensive reference and history book on what is measured and why. Measurement is one of humankind's oldest and most vital activities. By measuring height, speed, size, temperature, strength and many other factors, humans can compare, improve and progress. In fact, measurement is an essential tool for survival. A Measure of Everything is a wide-ranging and comprehensive guide to what is measured and why. The book begins when the basic measurements were as simple as more, less and enough. As societies evolved, relative measurements were no longer sufficient. Advances in language allowed more precise measurements. Short distances were measured in relation to parts of the human body. For example, the ancient measurement cubit was the length of a pharaoh's arm plus the width of his hand. As society and culture progress and change, so do measurements. The rise of astronomy and the sciences demanded more exact measurements. These measurements are typically named after the discovering scientist, e.g., henry, curie, watt, rutherford, fahrenheit. This book features 28 categories organized into three sections: Earth and Life Sciences: astronomy, distance, time, meteorology, medicine, and five others. Physical Sciences: chemistry, mathematics, physics, speed, weight, temperature, and three others. Technology and Leisure: computers, engineering, finance, food, textiles, and four others. A Measure of Everything is an informative and entertaining book that will appeal to a wide range of readers.
This volume, from an international authority on the subject, deals with the physical and instrumentation aspects of measurement science, the availability of major measurement tools, and how to use them. This book not only lays out basic concepts of electronic measurement systems, but also provides numerous examples and exercises for the student.·Ideal for courses on instrumentation, control engineering and physics ·Numerous worked examples and student exercises
This book provides a comprehensive introduction to the theory and practice of diagnostic classification models (DCMs), which are useful for statistically driven diagnostic decision making. DCMs can be employed in a wide range of disciplines, including educational assessment and clinical psychology. For the first time in a single volume, the authors present the key conceptual underpinnings and methodological foundations for applying these models in practice. Specifically, they discuss a unified approach to DCMs, the mathematical structure of DCMs and their relationship to other latent variable models, and the implementation and estimation of DCMs using Mplus. The book's highly accessible language, real-world applications, numerous examples, and clearly annotated equations will encourage professionals and students to explore the utility and statistical properties of DCMs in their own projects. This book will appeal to professionals in the testing industry; professors and students in educational, school, clinical, and cognitive psychology. It will also serve as a useful text in doctoral-level courses in diagnostic testing, cognitive diagnostic assessment, test validity, diagnostic assessment, advanced educational measurement, psychometrics, and item response theory
Biophysical Measurement in Experimental Social Science Research is an ideal primer for the experimental social scientist wishing to update their knowledge and skillset in the area of laboratory-based biophysical measurement. Many behavioral laboratories across the globe have acquired increasingly sophisticated biophysical measurement equipment, sometimes for particular research projects or for financial or institutional reasons. Yet the expertise required to use this technology and integrate the measures it can generate on human subjects into successful social science research endeavors is often scarce and concentrated amongst a small minority of researchers. This book aims to open the door to wider and more productive use of biophysical measurement in laboratory-based experimental social science research. Suitable for doctoral students through to established researchers, the volume presents examples of the successful integration of biophysical measures into analyses of human behavior, discussions of the academic and practical limitations of laboratory-based biophysical measurement, and hands-on guidance about how different biophysical measurement devices are used. A foreword and concluding chapters comprehensively synthesize and compare biophysical measurement options, address academic, ethical and practical matters, and address the broader historical and scientific context. Research chapters demonstrate the academic potential of biophysical measurement ranging fully across galvanic skin response, heart rate monitoring, eye tracking and direct neurological measurements. An extended Appendix showcases specific examples of device adoption in experimental social science lab settings. - Demonstrates the strengths and limitations of different tools, in terms of both research objectives and practicality - Provides hands-on guidance for device usage and data integration and assessment - Compares and contrasts the use of different biophysical data options for different research objectives and in different disciplines
Many psychological factors are little more than statistical descriptions of particular sets of data and have no real significance. Paul Kline uses his long and extensive knowledge of psychological measurement to argue that truly scientific forms of measurement could be developed to create a new psychometrics. This would transform the basis of psychology and change it from a social science to a pure science.