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

Empirical Findings on Quality and Comparability of Survey Data

This chapter reviews the empirical literature relevant to our focus on data quality and comparability. We start with a review of the findings on response quality, followed by an evaluation of previous approaches assessing such quality. We then turn our attention to the effects of the survey architecture on ...

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