Coverage Error in Data Collection Combining Mobile Surveys with Passive Measurement Using Apps: Data from a German National Survey

Autor/inn/en	Keusch, Florian; Bähr, Sebastian; Haas, Georg-Christoph; Kreuter, Frauke; Trappmann, Mark
Titel	Coverage Error in Data Collection Combining Mobile Surveys with Passive Measurement Using Apps: Data from a German National Survey
Quelle	In: Sociological Methods & Research, 52 (2023) 2, S.841-878 (38 Seiten) PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Keusch, Florian)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0049-1241
Schlagwörter	National Surveys; Computer Software; Telecommunications; Handheld Devices; Ownership; Data Collection; Error of Measurement; Research Problems; Labor Market; Public Policy; Probability; Poverty; Correlation; Foreign Countries; Participant Characteristics; Age Differences; Gender Differences; Germany + Suchen Sie Ihr Suchwort? Telekommunikationstechnik; Eigentum; Data capture; Datensammlung; Messfehler; Forschungskritik; Labour market; Arbeitsmarkt; Öffentliche Ordnung; Wahrscheinlichkeitsrechnung; Wahrscheinlichkeitstheorie; Armut; Korrelation; Ausland; Age; Difference; Age difference; Altersunterschied; Geschlechterkonflikt; Deutschland
Abstract	Researchers are combining self-reports from mobile surveys with passive data collection using sensors and apps on smartphones increasingly more often. While smartphones are commonly used in some groups of individuals, smartphone penetration is significantly lower in other groups. In addition, different operating systems (OSs) limit how mobile data can be collected passively. These limitations cause concern about coverage error in studies targeting the general population. Based on data from the Panel Study Labour Market and Social Security (PASS), an annual probability-based mixed-mode survey on the labor market and poverty in Germany, we find that smartphone ownership and ownership of smartphones with specific OSs are correlated with a number of sociodemographic and substantive variables. The use of weighting techniques based on sociodemographic information available for both owners and nonowners reduces these differences but does not eliminate them. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01