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Huth, M. ; Garavito, C.A.* ; Seep, L.* ; Cirera, L.* ; Saúte, F.* ; Sicuri, E.* ; Hasenauer, J.

Federated difference-in-differences with multiple time periods in DataSHIELD.

iScience 27:111025 (2024)
Verlagsversion DOI PMC
Open Access Gold
Creative Commons Lizenzvertrag
Difference-in-differences (DID) is a key tool for causal impact evaluation but faces challenges when applied to sensitive data restricted by privacy regulations. Obtaining consent can shrink sample sizes and reduce statistical power, limiting the analysis's effectiveness. Federated learning addresses these issues by sharing aggregated statistics rather than individual data, though advanced federated DID software is limited. We developed a federated version of the Callaway and Sant'Anna difference-in-differences (CSDID), integrated into the DataSHIELD platform, adhering to stringent privacy protocols. Our approach reproduces key estimates and standard errors while preserving confidentiality. Using simulated and real-world data from a malaria intervention in Mozambique, we demonstrate that federated estimates increase sample sizes, reduce estimation uncertainty, and enable analyses when data owners cannot share treated or untreated group data. Our work contributes to facilitating the evaluation of policy interventions or treatments across centers and borders.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Korrespondenzautor
Schlagwörter Computer Science ; Health Informatics ; Machine Learning
ISSN (print) / ISBN 2589-0042
e-ISSN 2589-0042
Zeitschrift iScience
Quellenangaben Band: 27, Heft: 11, Seiten: , Artikelnummer: 111025 Supplement: ,
Verlag Elsevier
Verlagsort Amsterdam ; Bosten ; London ; New York ; Oxford ; Paris ; Philadelphia ; San Diego ; St. Louis
Nichtpatentliteratur Publikationen
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Computational Biology (ICB)
Förderungen European Union
ORCHESTRA project
University of Bonn
German Research Foundation (Deutsche Forschungsgemeinschaft, DFG) under Germany's Excellence Strategy