Assessing the Quality of Survey Data

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  • Assessing the Quality of Survey Data Book Detail

  • Author : Jörg Blasius
  • Release Date : 2012-02-21
  • Publisher : SAGE
  • Genre : Social Science
  • Pages : 193
  • ISBN 13 : 1446258726
  • File Size : 54,54 MB

Assessing the Quality of Survey Data by Jörg Blasius PDF Summary

Book Description: This is a book for any researcher using any kind of survey data. It introduces the latest methods of assessing the quality and validity of such 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 exemplify how to detect all manner of non-substantive variation having sources such as a variety of response styles including acquiescence, respondents′ failure to understand questions, inadequate field work standards, interview fatigue, and even the manufacture of (partly) faked interviews.

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Assessing the Quality of Survey Data

Assessing the Quality of Survey Data

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This is a book for any researcher using any kind of survey data. It introduces the latest methods of assessing the quality and validity of such data by providin

Assessing the Quality of Survey Data

Assessing the Quality of Survey Data

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Total View : 7524 Views
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This is a book for any researcher using any kind of survey data. It introduces the latest methods of assessing the quality and validity of such data by providin

Analysis of Survey Data

Analysis of Survey Data

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This book is concerned with statistical methods for the analysis of data collected from a survey. A survey could consist of data collected from a questionnaire

Introduction to Survey Quality

Introduction to Survey Quality

File Size : 77,77 MB
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Peruse the history of survey research and the essential conceptsfor data quality. With an emphasis on total survey error, theauthors review principles and conce