2020/09/25 by Neta Barkay, Barkay, Neta, Curtiss Cobb +13 · 2 citations
Mathematics · Medicine · Social Sciences · #Computers and Society (cs.CY) #Data-Driven Disease Surveillance #FOS: Computer and information sciences #Social and Information Networks (cs.SI) #Statistical Methods and Bayesian Inference #Survey Methodology and Nonresponse
paper · pdf · doi:10.48550/arxiv.2009.14675
openalex publication_date 2020/09/25 · openalex created_date 2020/10/08 · openalex updated_date 2026/07/28
Facebook is partnering with academic institutions to support COVID-19 research. Currently, we are inviting Facebook app users in the United States to take a survey collected by faculty at Carnegie Mellon University (CMU) Delphi Research Center, and we are inviting Facebook app users in more than 200 countries or territories globally to take a survey collected by faculty at the University of Maryland (UMD) Joint Program in Survey Methodology (JPSM). As part of this initiative, we are applying best practices from survey statistics to design and execute two components: (1) sampling design and (2) survey weights, which make the sample more representative of the general population. This paper describes the methods we used in these efforts in order to allow data users to execute their analyses using the weights.