A privacy-preserving and computation-efficient federated algorithm for generalized linear mixed models to analyze correlated electronic health records data

• Zhiyu Yan,

  Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Writing – original draft

  Affiliation Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, United States of America

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• Kori S. Zachrison,

  Roles Formal analysis, Funding acquisition, Investigation, Supervision, Writing – review & editing

  Affiliations Department of Emergency Medicine, Massachusetts General Hospital, Boston, Massachusetts, United States of America, Harvard Medical School, Boston, Massachusetts, United States of America

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• Lee H. Schwamm,

  Roles Funding acquisition, Investigation, Supervision, Writing – review & editing

  Affiliations Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, United States of America, Harvard Medical School, Boston, Massachusetts, United States of America, Mass General Brigham, Boston, Massachusetts, United States of America

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• Juan J. Estrada,

  Roles Investigation, Writing – review & editing

  Affiliation Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, United States of America

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• Rui Duan

  Roles Conceptualization, Investigation, Methodology, Supervision, Writing – original draft

  * E-mail: rduan@hsph.harvard.edu

  Affiliation Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, United States of America

  https://orcid.org/0000-0002-9261-4864

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