Includes bibliographical references (p. [164]-172) and index.

Conceptualizing data quality : respondent attributes, study architecture, and institutional practices -- Empirical findings on quality and comparability of survey data -- Statistical techniques for data screening -- Institutional quality control practices -- Substantive or methodology-induced factors? : a comparison of PCA, CatPCA, and MCA solutions -- Item difficulty and response quality -- Questionnaire architecture -- Cognitive competencies and response quality.

"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."--Publisher's website.