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  "Title": "Bayesian Federated Inference",
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  "Authors@R": "c(person(given = \"Hassan\", family = \"Pazira\", email = \"hassan.pazira@radboudumc.nl\", \nrole = c(\"aut\", \"cre\"), comment = c(ORCID = \"0000-0002-4266-6877\")),\nperson(given = \"Emanuele\", family = \"Massa\", role = \"aut\",\ncomment = c(ORCID = \"0000-0001-5715-2572\")),\nperson(given = \"Marianne A.\", family = \"Jonker\", role = \"aut\",\ncomment = c(ORCID = \"0000-0003-0134-8482\")))",
  "Author": "Hassan Pazira [aut, cre]\n(<https://orcid.org/0000-0002-4266-6877>), Emanuele Massa [aut]\n(<https://orcid.org/0000-0001-5715-2572>), Marianne A. Jonker\n[aut] (<https://orcid.org/0000-0003-0134-8482>)",
  "Maintainer": "Hassan Pazira <hassan.pazira@radboudumc.nl>",
  "Description": "The Bayesian Federated Inference ('BFI') method combines\ninference results obtained from local data sets in the separate\ncenters. In this version of the package, the 'BFI' methodology\nis programmed for linear, logistic and survival regression\nmodels. For GLMs, see Jonker, Pazira and Coolen (2024)\n<doi:10.1002/sim.10072>; for survival models, see Pazira,\nMassa, Weijers, Coolen and Jonker (2025)\n<doi:10.48550/arXiv.2404.17464>; and for heterogeneous\npopulations, see Jonker, Pazira and Coolen (2025)\n<doi:10.1017/rsm.2025.6>.",
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      "title": "Bayesian Federated Inference",
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      "page": "BFI",
      "title": "Bayesian Federated Inference",
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        "bfi"
      ]
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        "summary.bfi"
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