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.
Our research on Survey Statistics
- 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
- Cornesse, Carina, Barbara Felderer, Marina Fikel, Ulrich Krieger, and Annelies G. Blom. 2022. "Recruiting a Probability-Based Online Panel via Postal Mail: Experimental Evidence." Social Science Computer Review 40 (5): 1259 - 1284. doi: https://doi.org/10.1177/08944393211006059.
- Quandt, Markus, and Antonia May. 2019. "Classifying a Large Number of Countries by their Populations’ Shares of Ethnic and Civic Types of National Identification." European Survey Research Association conferences, University of Zagreb, Zagreb.
- Quandt, Markus, and Antonia May. 2019. "Using Latent Class Analysis for testing the equivalence of multi-item scales across data from different survey programs. The example of National Identity types." Conference of the ‘Survey Data Recycling Project’: Building Multi-Source Databases for Comparative Analyses, Institute of Philosophy and Sociology of the Polish Academy of Sciences Warsaw, Poland, 2019-12-16.
- Daikeler, Jessica. 2019. The Application of Evidence-Based Methods in Survey Methodology: Inauguraldissertation zur Erlangung des akademischen Grades eines Doktors der Sozialwissenschaften der Universität Mannheim. Mannheim: Universität Mannheim .
- Gauly, Britta, Jessica Daikeler, Tobias Gummer, and Beatrice Rammstedt. 2020. "What’s my wage again? Comparing survey and administrative data to validate earning measures." International Journal of Social Research Methodology 23 (2): 215-228. doi: https://doi.org/10.1080/13645579.2019.1657691.
| Title | Start | End | Funder | |
|---|---|---|---|---|
| Keine Projekte gefunden. | ||||
Find out more about our consulting and services:
-
Data harmonization
Tools and topic-specific harmonized data for your research project
-
Harmonisation
Consulting on the harmonization of content elements and social-structural characteristics
-
Harmonizing and synthesizing partnership histories
A tool for harmonization and synthesis of couple biographical data.
-
Harmonizing substantive instruments
Consultation on harmonization of latent construct measurement instruments.
-
Imputation of Missing Values
We perform imputation of missing values for your complete data set or even selected variables
Contact persons
