Seit Kriegsbeginn sind mehr als eine Million Menschen aus der Ukraine nach Deutschland geflohen. Erste repräsentative Erkenntnisse über deren Lebenssituation und Zukunftspläne ermöglicht die Studie „Geflüchtete aus der Ukraine in Deutschland (IAB-BiB/FReDA-BAMF-SOEP-Befragung)“, eine gemeinsame Studie des Instituts für Arbeitsmarkt- und Berufsforschung (IAB), des Bundesinstituts für Bevölkerungsforschung (BiB), des Forschungszentrums des Bundesamts für Migration und Flüchtlinge (BAMF-FZ) und des Sozio-oekonomischen Panels (SOEP) am Deutschen Institut für Wirtschaftsforschung (DIW Berlin). Es wurden für diese Studie 11.225 geflüchtete Ukrainerinnen und Ukrainer in der Zeit zwischen August und Oktober 2022 befragt.
Interviewer (mis)behavior has been shown to change with interviewers’ professional experience (general experience) and experience gained during the field period (survey experience). We extend this study by using both types of experiences to analyze interviewer effects on a core quality indicator: interview duration. To understand whether the effect of interviewer experience on duration is driven by increased efficiency or deviant behavior—both mechanisms of shorter interview durations—we additionally examine the triggering rate of filter questions to avoid burdensome follow-up questions and response differentiation over the field period. Using multilevel models and data from a large-scale survey on a special and difficult-to-interview population of refugees in Germany, we find that interview duration decreases with increasing survey experience, particularly among the generally inexperienced interviewers. However, this effect is not found for the triggering rate and response differentiation. The results are robust to different sample and model specifications. We conclude that the underlying mechanism driving interview duration is related to increasing efficiency, and not deviant behavior.
Deviant interviewer behavior is a potential hazard of interviewer-administered surveys, with interviewers fabricating entire interviews as the most severe form. Various statistical methods (e.g., cluster analysis) have been proposed to detect falsifiers. These methods often rely on falsification indicators aiming to measure differences between real and falsified data. However, due to a lack of real-world data, empirical evaluations and comparisons of different statistical methods and falsification indicators are scarce. Using a large-scale nationally representative refugee survey in Germany with known fraudulent interviews, this study tests, evaluates, and compares statistical methods for identifying falsified data. We investigate the use of new and existing falsification indicators as well as multivariate detection methods for combining them. Additionally, we introduce a new and easy-to-use multivariate detection method that overcomes practical limitations of previous methods. We find that the vast majority of used falsification indicators successfully measure differences between falsifiers and nonfalsifiers, with the newly proposed falsification indicators outperforming some existing indicators. Furthermore, different multivariate detection methods perform similarly well in detecting the falsifiers.
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