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  "Type": "Package",
  "Title": "Bayesian Individual Patient Data Meta-Analysis using 'JAGS'",
  "Version": "0.3",
  "Date": "2022-05-30",
  "Authors@R": "c( \nperson(\"Michael\", \"Seo\", email = \"swj8874@gmail.com\", role = c(\"aut\", \"cre\")))",
  "Description": "We use a Bayesian approach to run individual patient data\nmeta-analysis and network meta-analysis using 'JAGS'. The\nmethods incorporate shrinkage methods and calculate\npatient-specific treatment effects as described in Seo et al.\n(2021) <DOI:10.1002/sim.8859>. This package also includes\nuser-friendly functions that impute missing data in an\nindividual patient data using mice-related packages.",
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  "Encoding": "UTF-8",
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  "Repository": "https://mikejseo.r-universe.dev",
  "Date/Publication": "2022-06-03 18:04:16 UTC",
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      "title": "bipd: A package for individual patient data meta-analysis using 'JAGS'",
      "topics": [
        "bipd-package"
      ]
    },
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      "page": "add.mcmc",
      "title": "Convenient function to add results (i.e. combine mcmc.list)",
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        "add.mcmc"
      ]
    },
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      "page": "findMissingPattern",
      "title": "Find missing data pattern in a given data",
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        "findMissingPattern"
      ]
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      ]
    },
    {
      "page": "generate_ipdnma_example",
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      "topics": [
        "generate_ipdnma_example"
      ]
    },
    {
      "page": "generate_sysmiss_ipdma_example",
      "title": "Generate a simulated IPD-MA data with systematically missing covariates",
      "topics": [
        "generate_sysmiss_ipdma_example"
      ]
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      "title": "Run the model using the ipd object",
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        "ipd.run"
      ]
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      "page": "ipd.run.parallel",
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    },
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