When survey science met web tracking: Presenting an error framework for metered data
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DOI: 10.1111/rssa.12956
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- Jake M. Hofman & Duncan J. Watts & Susan Athey & Filiz Garip & Thomas L. Griffiths & Jon Kleinberg & Helen Margetts & Sendhil Mullainathan & Matthew J. Salganik & Simine Vazire & Alessandro Vespignani, 2021. "Integrating explanation and prediction in computational social science," Nature, Nature, vol. 595(7866), pages 181-188, July.
- D. L. Oberski & A. Kirchner & S. Eckman & F. Kreuter, 2017. "Evaluating the Quality of Survey and Administrative Data with Generalized Multitrait-Multimethod Models," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(520), pages 1477-1489, October.
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- repec:osf:socarx:n9rx3_v1 is not listed on IDEAS
- Camilla Salvatore, 2023. "Inference with non-probability samples and survey data integration: a science mapping study," METRON, Springer;Sapienza Università di Roma, vol. 81(1), pages 83-107, April.
- Keusch, Florian & Pankowska, Paulina & Cernat, Alexandru & Bach, Ruben L., 2023. "Do you have two minutes to talk about your data? Willingness to participate and nonparticipation bias in Facebook data donation," SocArXiv n9rx3, Center for Open Science.
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