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  <titleInfo>
    <title>Assessing the quality of survey data</title>
  </titleInfo>
  <name type="personal">
    <namePart>Blasius, Jörg</namePart>
    <namePart type="date">1957-</namePart>
    <role>
      <roleTerm authority="marcrelator" type="text">creator</roleTerm>
    </role>
  </name>
  <name type="personal">
    <namePart>Thiessen, Victor.</namePart>
  </name>
  <typeOfResource>text</typeOfResource>
  <genre authority="marc">bibliography</genre>
  <originInfo>
    <place>
      <placeTerm type="code" authority="marccountry">enk</placeTerm>
    </place>
    <place>
      <placeTerm type="text">London</placeTerm>
    </place>
    <place>
      <placeTerm type="text">Thousand Oaks, Calif</placeTerm>
    </place>
    <publisher>Sage Publications</publisher>
    <dateIssued>2012</dateIssued>
    <issuance>monographic</issuance>
  </originInfo>
  <language>
    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
  </language>
  <physicalDescription>
    <form authority="marcform">print</form>
    <extent>xi, 174 p : ill ; 25 cm.</extent>
  </physicalDescription>
  <abstract>"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.</abstract>
  <tableOfContents>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.</tableOfContents>
  <note type="statement of responsibility">Jörg Blasius &amp; Victor Thiessen.</note>
  <note>Includes bibliographical references (p. [164]-172) and index.</note>
  <subject authority="lcsh">
    <topic>Social surveys</topic>
    <topic>Methodology</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Social sciences</topic>
    <topic>Statistical methods</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Social sciences</topic>
    <topic>Research</topic>
    <topic>Methodology</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Correspondence analysis (Statistics)</topic>
  </subject>
  <classification authority="lcc">HM538 .B57 2012</classification>
  <classification authority="ddc" edition="23">001.433</classification>
  <identifier type="isbn">1849203326</identifier>
  <identifier type="isbn">9781849203326 :</identifier>
  <identifier type="isbn">1849203318</identifier>
  <identifier type="isbn">9781849203319</identifier>
  <identifier type="lccn">2011932180</identifier>
  <recordInfo>
    <recordCreationDate encoding="marc">110615</recordCreationDate>
    <recordChangeDate encoding="iso8601">20230921135304.0</recordChangeDate>
    <recordIdentifier source="OCoLC">0000031078</recordIdentifier>
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