Synopsis
This book introduces the latest methods for assessing the quality and validity of survey data by providing new ways of interpreting variation and measuring error. By practically and accessibly demonstrating these techniques, especially those derived from Multiple Correspondence Analysis, the authors develop screening procedures to search for variation in observed responses that do not correspond with actual differences between respondents. Using well-known international data sets, the authors show how to detect all manner of non-substantive variation from response styles including acquiescence, respondents′ failure to understand questions, inadequate field work standards, interview fatigue, and even the manufacture of (partly) faked interviews."synopsis" may belong to another edition of this title.
About the Author
Jörg Blasius is a professor of Sociology at the Institute for Political Science and Sociology, University of Bonn, Germany. His research interests are mainly focused on explorative data analysis, especially correspondence analysis and related methods, data collection methods, sociology of lifestyles, and urban sociology. He is a coeditor of the SAGE Series “Survey Research Methods in the Social Sciences.” Together with Michael Greenacre (University Pompeu Fabra, Barcelona), he founded Carme (Correspondence Analysis and Related Methods Network, see www.carme-n.org). From 1998 to 2016, he belonged to the Board of RC33 (Research Committee on Logic and Methodology in Sociology) of the ISA (International Sociological Association), from 2006 to 2010 he served as president. Website: https://www.politik-soziologie.uni-bonn.de/de/personal/Prof.-Dr.-Joerg-Blasius
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Assessing the Quality of Survey Data (Research Methods for Social Scientists)
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Kartoniert / Broschiert. Condition: New. This book, for all researchers using survey data, presents new ways to assess the data s quality and reliability.Über den AutorJoerg Blasius is a professor of Sociology at the Institute for Political Science and Sociology,. Seller Inventory # 597102640