(2019):
Studying Integration from Adolescence to Early Adulthood: Design, Content, and Research Potential of the CILS4EU-DE Data.
European Sociological Review, 35, Heft 2, S. 280–297.
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325 Ergebnisse
(2019):
A Longitudinal Framework for Predicting Nonresponse in Panel Surveys.
Ithaca, NY
[arXiv preprint]
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(2019):
Tree-based machine learning methods for survey research.
Survey Research Methods, 13, Heft 1, S. 73-93.
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(2019):
Coverage and nonparticipation error in smartphone data collection.
[AAPOR 74th Annual Conferernce, Toronto, 16. bis 19. Mai 2019]
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(2019):
Impact of response scale features on survey responses to factual/behavioral questions.
S. 131-149 in:
Paul J. Lavrakas, Edith de Leeuw, Allyson Holbrook, Courtney Kennedy, Michael W. Traugott, Brady T. West
(Hrsg.)
Experimental Methods in Survey Research: Techniques that Combine Random Sampling with Random Assignment.
Hoboken, NJ:
Wiley.
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(2019):
Willingness to participate in passive mobile data collection.
Public Opinion Quarterly, 83, Heft S1, S. 210-235.
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(2019):
Social desirability in passive mobile data collection.
[8th Conference of the European Survey Research Association, Zagreb, 15. bis 19. Juli 2019]
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(2019):
Enriching an ongoing panel survey with mobile phone measures: The IAB-SMART study.
[DAGStat Conference 2019, Munich, 18. bis 22. März 2019]
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(2019):
Mobile Datenerhebung in einem Panel: Die IAB-SMART Studie.
[Gemeinsame Tagung der Arbeitsgemeinschaft Sozialwissenschaftlicher Institute (ASI) und der DGS-Methoden Sektion, Köln, 15. bis 16. November 2019]
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(2019):
Tracking changes of mind through mouse movements.
[49th Annual Meeting of the Society for Computers in Psychology, Montréal, 14. November 2019]
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