The SDR analytic framework draws on the Total Survey Error, Survey Quality Monitoring and Fitness for Intended Use approaches to define survey quality as methodological errors and biases that stem from deviations from standards of data collection, processing, and releasing \u2013 standards available in the specialized methodological literature and promoted by professional organizations of public opinion and marketing research.<\/p>\n\n\n\n
This definition allows to break the complex concept of survey data quality into 3 dimensions: <\/p>\n\n\n\n
a) Quality of surveys as reflected in the survey documentation, <\/strong>sinceinadequate information in documentation reduces confidence in the data;<\/p>\n\n\n\n b) Quality of the data records<\/strong> in national datasets (i.e. computer files), since occurrence of errors can lead to distortion of empirical results;<\/p>\n\n\n\n c) Degree of consistency between documentation <\/strong>and data records<\/strong> in the computer file, since occurrence of processing errors can affect the overall usability of the survey.<\/p>\n\n\n\n For each dimension, we develop specific operational definitions that we use to measure quality elements of the source surveys.<\/p>\n\n\n\n For publications on survey data quality in the SDR analytic framework:<\/p>\n\n\n\n Slomczynski, Kazimierz M and Irina Tomescu-Dubrow. 2018. \u201cBasic Principles of Survey Data Recycling.\u201d Ch. 43; p. 937-962 in Advances in Comparative Survey Methodology: Multinational, Multiregional and Multicultural Contexts<\/em><\/a> (3MC)<\/em>, T.P. Johnson, B-E Pennell, I. A. L. Stoop, & B. Dorer (eds), Wiley Hoboken, New Jersey<\/p>\n\n\n\n Ko\u0142czy\u0144ska, Marta, & Schoene, Matthew. 2018. \u201cSurvey Data Harmonization and the Quality of Data Documentation in Cross-national Surveys.\u201d In T. P. Johnson, B.-E. Pennell, I. Stoop, & B. Dorer (Eds.), Advances in Comparative Survey Methodology: Multinational, Multiregional and Multicultural Contexts (3MC)<\/em><\/a> (pp. 963\u2013984). John Wiley & Sons, Ltd.<\/p>\n\n\n\n Oleksiyenko, Olena, Wysmulek, Ilona & Vangeli, Anastas. 2018. \u201cIdentification of Processing Errors in Cross\u2010national Surveys.\u201d In Johnson, T.P, Pennell, B.-E., Stoop, I.A., & Dorer, B. (Eds.), Advances in Comparative Survey Methodology: Multinational, Multiregional and Multicultural Contexts (3MC)<\/em><\/a> (pp. 985\u20131010). John Wiley & Sons, Inc.<\/p>\n\n\n\n Zieli\u0144ski, Marcin. W., Powa\u0142ko, Przemek., and Ko\u0142czy\u0144ska, Marta. 2018. \u201cThe Past, Present, and Future of Statistical Weights in International Survey Projects: Implications for Survey Data Harmonization.\u201d Advances in Comparative Survey Methodology: Multinational, Multiregional and Multicultural Contexts (3MC)<\/em><\/a>, 1035\u20131052.<\/p>\n\n\n\n Slomczynski, Kazimierz M., Przemek Powalko and Tadeusz Krauze. 2017. \u201cNon-unique Records in International Survey Projects: The Need for Extending Data Quality Control<\/a>.\u201d Survey Research Methods<\/em> 11(1): 1-16.<\/p>\n","protected":false},"excerpt":{"rendered":" The SDR analytic framework draws on the Total Survey Error, Survey Quality Monitoring and Fitness for Intended Use approaches to define survey quality as methodological errors and biases that stem from deviations from standards of data collection, processing, and releasing …<\/p>\n