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  "Description": "Dual interfaces, graphical and programmatic, designed for\nintuitive applications of Multilevel Regression and\nPoststratification (MRP). Users can apply the method to a\nvariety of datasets, from electronic health records to sample\nsurvey data, through an end-to-end Bayesian data analysis\nworkflow. The package provides robust tools for data cleaning,\nexploratory analysis, flexible model building, and insightful\nresult visualization. For more details, see Si et al. (2020)\n<https://www150.statcan.gc.ca/n1/en/pub/12-001-x/2020002/article/00003-eng.pdf?st=iF1_Fbrh>\nand Si (2025) <doi:10.1214/24-STS932>.",
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      "topics": [
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      "topics": [
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        "MRPModel-method-check_estimate_exists"
      ]
    },
    {
      "page": "MRPModel-method-check_fit_exists",
      "title": "Check if model has been fitted",
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        "check_fit_exists",
        "MRPModel-method-check_fit_exists"
      ]
    },
    {
      "page": "MRPModel-method-diagnostics",
      "title": "Return sampling diagnostics",
      "topics": [
        "diagnostics",
        "MRPModel-method-diagnostics"
      ]
    },
    {
      "page": "MRPModel-method-fit",
      "title": "Fit multilevel regression model using cmdstanr",
      "topics": [
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        "MRPModel-method-fit"
      ]
    },
    {
      "page": "MRPModel-method-formula",
      "title": "Return model formula",
      "topics": [
        "formula",
        "MRPModel-method-formula"
      ]
    },
    {
      "page": "MRPModel-method-log_lik",
      "title": "Create inputs for leave-one-out cross-validation",
      "topics": [
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        "MRPModel-method-log_lik"
      ]
    },
    {
      "page": "MRPModel-method-metadata",
      "title": "Return model metadata.",
      "topics": [
        "metadata",
        "MRPModel-method-metadata"
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    },
    {
      "page": "MRPModel-method-model_spec",
      "title": "Return model specification",
      "topics": [
        "model_spec",
        "MRPModel-method-model_spec"
      ]
    },
    {
      "page": "MRPModel-method-poststratify",
      "title": "Run poststratification to generate population estimates",
      "topics": [
        "MRPModel-method-poststratify",
        "poststratify"
      ]
    },
    {
      "page": "MRPModel-method-ppc",
      "title": "Create input for posterior predictive check",
      "topics": [
        "MRPModel-method-ppc",
        "ppc"
      ]
    },
    {
      "page": "MRPModel-method-save",
      "title": "Save model object to file",
      "topics": [
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        "save"
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    },
    {
      "page": "MRPModel-method-stan_code",
      "title": "Return model Stan code.",
      "topics": [
        "MRPModel-method-stan_code",
        "stan_code"
      ]
    },
    {
      "page": "MRPModel-method-summary",
      "title": "Return posterior summary table",
      "topics": [
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        "summary"
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    },
    {
      "page": "MRPWorkflow",
      "title": "MRPWorkflow objects",
      "topics": [
        "MRPWorkflow"
      ]
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    {
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      "title": "Compare models using LOO-CV",
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        "MRPWorkflow-method-compare_models"
      ]
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    {
      "page": "MRPWorkflow-method-covar_hist",
      "title": "Create geographic covariate distribution histogram",
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        "MRPWorkflow-method-covar_hist"
      ]
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    {
      "page": "MRPWorkflow-method-create_model",
      "title": "Create a new MRPModel object",
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        "MRPWorkflow-method-create_model"
      ]
    },
    {
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        "MRPWorkflow-method-demo_bars"
      ]
    },
    {
      "page": "MRPWorkflow-method-estimate_map",
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        "MRPWorkflow-method-estimate_map"
      ]
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        "MRPWorkflow-method-estimate_plot"
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    {
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      "topics": [
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    {
      "page": "MRPWorkflow-method-outcome_plot",
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      "page": "MRPWorkflow-method-pp_check",
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      "topics": [
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      "page": "run_app",
      "title": "Run the Shiny Application",
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      "title": "More examples of R6 classes",
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