Survey Data Collection and Integration (PDF)
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Statistical surveys represent an important source of scientific knowledge and a valid decision support tool in many fields, from social studies to economics, market research, health studies, and others. Scientists have tackled most of the methodological issues concerning surveys and the scientific literature offers excellent proposals for planning and conducting surveys. Nevertheless, surveys often require the achievement of aims that either deviate from the methodology or do not have a specific solution at all.
This book focuses on survey theory and applications, providing insight and innovative solutions to face problems in data collection and integration, complex sample design, opinion questionnaire design, and statistical estimation.
Formal rigour and simple language, together with real-life examples, will make the book suitable to both practitioners involved in applied research and to academics interested in scientific developments in the survey field.
Luigi Fabbris is a full professor in Social Statistics at the Statistics Department, the University of Padua, Italy, where he lectures in Survey Methodology and Social Statistics. His research fields are multivariate analysis, survey sampling and questionnaire design; he was also active in social indicators, nexuses between education and work, social conditions of women, immigrants, the elderly and the homeless.
- 2012, 2012, 156 Seiten, Englisch
- Herausgegeben: Cristina Davino, Luigi Fabbris
- Verlag: Springer-Verlag GmbH
- ISBN-10: 3642213081
- ISBN-13: 9783642213083
- Erscheinungsdatum: 22.10.2012
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- Größe: 4.86 MB
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“The book under review deals with problems that require practical solutions that either deviate from the traditional methodology or do not have a specific solution at all. The methodology described in this volume is very valuable as it provides additional statistical tools for generating data and extracting the necessary information. … The book Survey Data Collection and Integration is a valuable addition to the expanding repertoire of statistical methodology.” (C. R. Rao, Technometrics, Vol. 56 (1), January, 2014)
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