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  "Title": "IPW and Mean Score Methods for Time-Course Missing Data",
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  "Authors@R": "c(person((\"Atanu\"), \"Bhattacharjee\",\nemail=\"atanustat@gmail.com\",\nrole=c(\"aut\", \"cre\",\"ctb\")),\nperson((\"Bhrigu Kumar\"), \"Rajbongshi\", role=c(\"aut\",\"ctb\")),\nperson((\"Gajendra K\"), \"Vishwakarma\", role=c(\"aut\",\"ctb\")))",
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  "Description": "Contains functions for data analysis of Repeated\nmeasurement using GEE. Data may contain missing value in\nresponse and covariates. For parameter estimation through\nFisher Scoring algorithm, Mean Score and Inverse Probability\nWeighted method combining with Multiple Imputation are used\nwhen there is missing value in covariates/response. Reference\nfor mean score method, inverse probability weighted method is\nWang et al(2007)<doi:10.1093/biostatistics/kxl024>.",
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        "Visit",
        "C6kine",
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        "ActivinRIIA",
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        "AgRP",
        "ALCAM"
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      "title": "Fit a geeglm model using meanScore",
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        "MeanScore"
      ]
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      "title": "Fit a geeglm model using miAIPW",
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        "miAIPW"
      ]
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      "page": "miSIPW",
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