Improving Data Quality with Sociodemographic Matching?: About the Effects and Implications of Age and Gender Matching in Face-to-Face Interviews

Faculty/Professorship: Leibniz Institute for Educational Trajectories (LIfBi) 
Author(s): Bittmann, Felix  
Publisher Information: Bamberg : Otto-Friedrich-Universität
Year of publication: 2022
Pages: 242-260
Source/Other editions: Journal of Applied Social Science, 16 (2022), 1, S. 242-260 - ISSN: 1937-0245
is version of: 10.1177/1936724421998257
Year of first publication: 2022
Language(s): English
Licence: Creative Commons - CC BY-NC - Attribution - NonCommercial 4.0 International 
URN: urn:nbn:de:bvb:473-irb-548913
According to the theory of liking, data quality might be improved in face-to-face survey settings when there is a high degree of similarity between respondents and interviewers, for example, with regard to gender or age. Using two rounds of European Social Survey data from 25 countries including more than 70,000 respondents, this concept is tested for the dependent variables amount of item nonresponse, reluctance to answer, and the probability that a third adult person is interfering with the interview. The match between respondents and interviewers is operationalized using the variables age and gender and their statistical interactions to analyze how this relates to the outcomes. While previous studies can be corroborated, overall effect sizes are small. In general, item nonresponse is lower when a male interviewer is conducting the interview. For reluctance, there are no matching effects at all. Regarding the presence of other adults, only female respondents profit from a gender match, while age is without any effect. The results indicate that future surveys should weigh the costs and benefits of sociodemographic matching as advantages are probably small.
GND Keywords: Umfrage; Interview; Fehlerquelle; Datenqualität
Keywords: survey quality, gender matching, theory of liking,, European Social Survey, statistical matching
DDC Classification: 150 Psychology  
RVK Classification: CM 2200   
Type: Article
Release Date: 8. August 2022

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