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Survey Statistics

In the field of survey statistics, we investigate different aspects of the quality of surveys. Sample design, in particular sample size and sample composition, have a direct impact on the representativeness of survey results. Unit nonresponse and item nonresponse pose further challenges to data quality. The research activities in the field of survey statistics therefore focus on problems and solutions associated with random sampling. These are also investigated in several third-party funded projects.

Research topics are in particular:

  • Drawing procedures for complex sample designs
  • Nonresponse (bias) analysis
  • Weighting procedures for survey designs
  • Imputation of missing values
  • Variance estimation under complex sample designs and imputation of missing values
  • Application of machine learning methods in survey statistics
  • König, Christian, Jette Schröder, and Erich Wiegand, ed. 2017. Big Data: Chancen, Risiken, Entwicklungstendenzen. Schriftenreihe der ASI - Arbeitsgemeinschat Sozialwissenschaftlicher Institute.
  • Massing, Natascha, and Silke L. Schneider. 2017. "Symposium VII: The social context of skills: Improving the PIAAC Background Questionnaire." PIAAC Research Conference, 05.04.2017.
  • Massing, Natascha, and Silke L. Schneider. 2017. "Education & Training - What is being Measured and What Needs to be Improved." PIAAC Research Conference, 05.04.2017.
  • Schneider, Silke L.. 2017. "Poster on Quality of the Educational Attainment Measures in OECD’s PIAAC Study." RC28 Spring Meeting 2017 - Social Inequality and Mobility Revisited – Challenges Through Recent Demographic Change, 30.03.2017.
  • Schneider, Silke L.. 2017. "Cross-national measurement of educational attainment and classification using ISCED." CIDER Fall Workshop, 18.09.2017.