Source Survey Quality in SDR
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 – standards available in the specialized methodological literature and promoted by professional organizations of public opinion and marketing research.
This definition allows to break the complex concept of survey data quality into 3 dimensions:
a) Quality of surveys as reflected in the survey documentation, sinceinadequate information in documentation reduces confidence in the data;
b) Quality of the data records in national datasets (i.e. computer files), since occurrence of errors can lead to distortion of empirical results;
c) Degree of consistency between documentation and data records in the computer file, since occurrence of processing errors can affect the overall usability of the survey.
For each dimension, we develop specific operational definitions that we use to measure quality elements of the source surveys.
For publications on survey data quality in the SDR analytic framework:
Slomczynski, Kazimierz M and Irina Tomescu-Dubrow. 2018. “Basic Principles of Survey Data Recycling.” Ch. 43; p. 937-962 in Advances in Comparative Survey Methodology: Multinational, Multiregional and Multicultural Contexts (3MC), T.P. Johnson, B-E Pennell, I. A. L. Stoop, & B. Dorer (eds), Wiley Hoboken, New Jersey
Kołczyńska, Marta, & Schoene, Matthew. 2018. “Survey Data Harmonization and the Quality of Data Documentation in Cross-national Surveys.” In T. P. Johnson, B.-E. Pennell, I. Stoop, & B. Dorer (Eds.), Advances in Comparative Survey Methodology: Multinational, Multiregional and Multicultural Contexts (3MC) (pp. 963–984). John Wiley & Sons, Ltd.
Oleksiyenko, Olena, Wysmulek, Ilona & Vangeli, Anastas. 2018. “Identification of Processing Errors in Cross‐national Surveys.” In Johnson, T.P, Pennell, B.-E., Stoop, I.A., & Dorer, B. (Eds.), Advances in Comparative Survey Methodology: Multinational, Multiregional and Multicultural Contexts (3MC) (pp. 985–1010). John Wiley & Sons, Inc.
Zieliński, Marcin. W., Powałko, Przemek., and Kołczyńska, Marta. 2018. “The Past, Present, and Future of Statistical Weights in International Survey Projects: Implications for Survey Data Harmonization.” Advances in Comparative Survey Methodology: Multinational, Multiregional and Multicultural Contexts (3MC), 1035–1052.
Slomczynski, Kazimierz M., Przemek Powalko and Tadeusz Krauze. 2017. “Non-unique Records in International Survey Projects: The Need for Extending Data Quality Control.” Survey Research Methods 11(1): 1-16.