The utility of auxiliary data for survey response modeling: Evidence from the German Internet Panel


Cornesse, Carina


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DOI: https://doi.org/10.13094/SMIF-2020-00008
URL: https://madoc.bib.uni-mannheim.de/59273
Additional URL: https://surveyinsights.org/?p=11849
URN: urn:nbn:de:bsz:180-madoc-592737
Document Type: Article
Year of publication: 2020
The title of a journal, publication series: Survey Methods : Insights from the Field
Volume: 2020
Issue number: Special issue
Page range: 1-9
Place of publication: Lausanne
Publishing house: Swiss Found. for Research in Social Sciences
ISSN: 2296-4754
Related URLs:
Publication language: English
Institution: Außerfakultäre Einrichtungen > Mannheim Centre for European Social Research - Research Department B
Außerfakultäre Einrichtungen > Leibniz-Institut für Sozialwissenschaften (GESIS)
Außerfakultäre Einrichtungen > SFB 884
Pre-existing license: Creative Commons Attribution 4.0 International (CC BY 4.0)
Subject: 300 Social sciences, sociology, anthropology
Abstract: Auxiliary data are becoming more important as nonresponse rates increase and new fieldwork monitoring and respondent targeting strategies develop. In many cases, auxiliary data are collected or linked to the gross sample to predict survey response. If the auxiliary data have high predictive power, the response models can meaningfully inform survey operations as well as post-survey adjustment procedures. In this paper, I examine the utility of different sources of auxiliary data (sampling frame data, interviewer observations, and micro-geographic area data) for modeling survey response in a probability-based online panel in Germany. I find that the utility of each of these data sources is challenged by a number of concerns (scarcity, missing data, transparency issues, and high levels of aggregation) and that none of the auxiliary data are associated with survey response to any substantial degree.

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ORCID: Cornesse, Carina ORCID: 0000-0002-5437-2999

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