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Identifying Pertinent Variables for Nonresponse Follow-Up Surveys. Lessons Learned from 4 Cases in Switzerland

Type of publication Peer-reviewed
Publikationsform Original article (peer-reviewed)
Author Vandenplas Caroline, Joye Dominique, Ernst Stähli Michèle, Pollien Alexandre,
Project European Social Survey 2014+2016
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Original article (peer-reviewed)

Journal Survey Research Methods
Volume (Issue) 9(3)
Page(s) 141 - 158
Title of proceedings Survey Research Methods
DOI 10.18148/srm/2015.v9i3.6138

Open Access

URL https://ojs.ub.uni-konstanz.de/srm/article/view/6138
Type of Open Access Publisher (Gold Open Access)

Abstract

All social surveys suffer from different types of errors, of which one of the most studied is non-response bias. Non-response bias is a systematic error that occurs because individuals differ in their accessibility and propensity to participate in a survey according to their own characteristics as well as those from the survey itself. The extent of the problem heavily depends on the correlation between response mechanisms and key survey variables. However, non-response bias is difficult to measure or to correct for due to the lack of relevant data about the whole target population or sample. In this paper, non-response follow-up surveys are considered as a possible source of information about non-respondents. Non-response follow-ups, however, suffer from two methodological issues: they themselves operate through a response mechanism that can cause potential non-response bias, and they pose a problem of comparability of measure, mostly because the survey design differs between main survey and non-response follow-up. In order to detect possible bias, the survey variables included in non-response surveys have to be related to the mechanism of participation, but not be sensitive to measurement effects due to the different designs. Based on accumulated experience of four similar non-response follow-ups, we studied the survey variables that fulfill these conditions. We differentiated socio-demographic variables that are measurement-invariant but have a lower correlation with non-response and variables that measure attitudes, such as trust, social participation, or integration in the public sphere, which are more sensitive to measurement effects but potentially more appropriate to account for the non-response mechanism. Our results show that education level, work status, and living alone, as well as political interest, satisfaction with democracy, and trust in institutions are pertinent variables to include in non-response follow-ups of general social surveys.
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