Abstract
Using mixed-mode data collection is becoming a mainstream way of conducting longitudinal surveys. However, interviewing the same units in a mixed-mode longitudinal design can lead to respondents switching between modes over time. As a result, mode switching behaviors can be correlated with non-response and potentially influence survey responses and estimates of change in longitudinal analyses. This paper investigates the patterns by which people transition from one mode of interview to another in a nationally-representative, sequential mixedmode (Web and face-to-face) longitudinal study. Using mixed-mode waves 5-10 of the Understanding Society Innovation Panel, we perform a latent class analysis on respondents and their mode switching behaviors. We identify five distinct classes of respondents: Face-to-face respondents, Web respondents, Face to face/late drop-offs, Single mode/early drop-offs and Switchers. Furthermore, we show that these classes differ with respect to respondent characteristics and significantly contribute to the prediction of future wave participation and mode of response, even after controlling for socio-demographic characteristics, interview mode at the previous wave, and previous non-response behavior. Practical implications of these results are discussed and possible strategies to use this information for targeting and correcting for non-response in longitudinal studies are proposed.
Dokumententyp: | Zeitschriftenartikel |
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Fakultät: | Mathematik, Informatik und Statistik > Statistik |
Themengebiete: | 500 Naturwissenschaften und Mathematik > 510 Mathematik |
ISSN: | 1864-3361 |
Sprache: | Englisch |
Dokumenten ID: | 97400 |
Datum der Veröffentlichung auf Open Access LMU: | 05. Jun. 2023, 15:25 |
Letzte Änderungen: | 05. Jun. 2023, 15:25 |