Measurement In The Social Sciences

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

This book proposes a revolutionary new theory of construct measurement – called C-OAR-SE – for the social sciences. The acronym is derived from the following key elements: construct definition; object representation; attribute classification; rater entity identification; selection of item type; enumeration and scoring. The new theory is applicable to the design of measures of constructs in: • Management • Marketing • Information Systems • Organizational Behavior • Psychology • Sociology C-OAR-SE is a rationally rather than empirically-based theory and procedure. It can be used for designing measures of the most complex and also the most basic constructs that we use in social science research. C-OAR-SE is a radical alternative to the traditional empirically-based psychometric approach, and a considerable amount of the book’s content is devoted to demonstrating why the psychometric approach does not produce valid measures. The book argues that the psychometric approach has resulted in many misleading findings in the social sciences and has led to erroneous acceptance – or rejection – of many of our main theories and hypotheses, and that the C-OAR-SE approach to measurement would correct this massive problem. The main purpose of this book is to introduce and explain C-OAR-SE construct measurement theory in a way that will be understood by all social science researchers and that can be applied to designing new, more valid measures. Featuring numerous examples, practical applications, end-of-chapter questions, and appendices, the book will serve as an essential resource for students and professional researcher alike.

Revised edition of the author's Social science concepts, c2006.

This textbook is designed to bridge the gap between the theorist and the methodologist by presenting an integrated approach to measurement. By differentiating between random and systematic error, it conveys both statistical techniques and their theoretical underpinnings essential to students of sociology and political science. Rather than developing new technical methods of new theoretical structures, Professors Zeller and Carmines provide thorough explanations of the assumptions, limitations and interpretations of previously established techniques and theories. Written at a level accessible to students of social science with some statistical training, the book does not presume a sophisticated mathematical background. By concentrating on synthesizing the methodological and theoretical realms, Zeller and Carmines demonstrate why measurement considerations are important to research and how measurement principles can be most effectively applied.

This original textbook provides a comprehensive and integrated approach to using quantitative methods in the social sciences. Thomas R Black guides the student and researcher through the minefield of potential problems that may be confronted, and it is this emphasis on the practical that distinguishes his book from others which focus exclusively on either research design and measurement or statistical methods. Focusing on the design and execution of research, key topics such as planning, sampling, the design of measuring instruments, choice of statistical text and interpretation of results are examined within the context of the research process. In a lively and accessible style, the student is introduced to researc design issues alongside statistical procedures and encouraged to develop analytical and decision-making skills.

Biophysical Measurement in Experimental Social Science Research: Theory and Practice demonstrates the use of biophysical measurement in laboratory-based experimental social science research and the ways biophysical measures can inform analyses of human behavior. Noting the practical limitations of laboratory-based biophysical measurement, its contributors provide hands-on guidance about biophysical measurement devices. Its Introductory and concluding chapters address ethics, measurement options, and historical and scientific contexts. Highlighting examples of device adoption in experimental social science lab settings, this book makes these tools understandable and accessible to all. Demonstrates the strengths and limitations of tools in both research objectives and practicality Provides hands-on guidance for device usage and data implementation, integration and assessment Compares and contrasts the uses of biophysical data in research objectives and disciplines

Are you a teacher or guidance counselor looking for an accessible reference guide? This revised edition of a popular 1993 anthology includes 120 tests and surveys, bringing together psychometric information about instruments developed to measure constructs in education and social sciences. Includes references to both published and unpublished instruments-scales, questionnaires, surveys, indices, and inventories-which otherwise would be painstakingly difficult for the researcher/teacher/counselor to locate.

Among the frustrations constantly confronting the social scientist are those associated with the general process of measurement. The importance of good measurement has long been recognized in principle, but it has often been neglected in practice in many of the social sciences. Now that the methodological tools of multivariate analysis, simultaneous-equation estimation, and causal modeling are diffused more widely into the social sciences, and now that the very serious implications of random and non-random measurement errors are being systematically investigated, it is all the more important that social scientists give top priority to the quality of their data and the clarity of their theoretical conceptualizations. The book is organized so that, one proceeds from problems of data collection to those of data analysis. It is not intended to be a complete work covering all types of measurement problems that have arisen in the social sciences. Instead, it represents a series of studies that are deemed to be crucial for the advancement of social science research but which have not received sufficient attention in most of the social sciences. The basic purpose is to stimulate further methodological research on measurement and to study the ways in which knowledge that has been accumulated in some fields may be generalized. Part I is concerned with applying scaling approaches developed in psychometrics to problems that arise in other social sciences. The focus is on finding better ways to ask questions of respondents so as to raise the level of measurement above that of simple ordinal scales. Part II focuses on multiple-indicator theory and strategies as applied to relatively complex models and to change data. In this section the emphasis shifts to how one analyzes fallible data through the construction of explicit measurement-error models. Part III deals with the statistical analysis of ordinal data, including the interpretation and empirical behaviors of various ordinal measures of association.