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    "run_maihda_app",
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        "escs",
        "math",
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        "low_math"
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      "table": true,
      "tojson": true
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      "title": "NHANES Health Data Subset for MAIHDA Use",
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        "Age",
        "Gender",
        "Race",
        "Education",
        "Poverty"
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      "table": true,
      "tojson": true
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      "title": "Simulated Health Data for MAIHDA Use",
      "object": "maihda_sim_data",
      "class": [
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      ],
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        "id",
        "gender",
        "race",
        "education",
        "age",
        "health_outcome",
        "binary_outcome"
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      "table": true,
      "tojson": true
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      "page": "calculate_pvc",
      "title": "Calculate Proportional Change in Between-Stratum Variance (PCV)",
      "topics": [
        "calculate_pvc"
      ]
    },
    {
      "page": "compare_maihda",
      "title": "Compare MAIHDA Models",
      "topics": [
        "compare_maihda"
      ]
    },
    {
      "page": "compare_maihda_groups",
      "title": "Compare MAIHDA Metrics Across Levels of a Grouping Variable",
      "topics": [
        "compare_maihda_groups"
      ]
    },
    {
      "page": "compute_maihda_ternary_data",
      "title": "Compute Ternary Data for MAIHDA Models",
      "topics": [
        "compute_maihda_ternary_data"
      ]
    },
    {
      "page": "fit_maihda",
      "title": "Fit MAIHDA Model",
      "topics": [
        "fit_maihda"
      ]
    },
    {
      "page": "maihda",
      "title": "Run a Complete MAIHDA Analysis",
      "topics": [
        "maihda"
      ]
    },
    {
      "page": "maihda_country_data",
      "title": "Cross-National Educational Achievement Data for MAIHDA",
      "topics": [
        "maihda_country_data"
      ]
    },
    {
      "page": "maihda_health_data",
      "title": "NHANES Health Data Subset for MAIHDA Use",
      "topics": [
        "maihda_health_data"
      ]
    },
    {
      "page": "maihda_sim_data",
      "title": "Simulated Health Data for MAIHDA Use",
      "topics": [
        "maihda_sim_data"
      ]
    },
    {
      "page": "maihda_ternary_plot",
      "title": "Generate Ternary Plot from MAIHDA Model",
      "topics": [
        "maihda_ternary_plot"
      ]
    },
    {
      "page": "make_strata",
      "title": "Create Strata from Multiple Variables",
      "topics": [
        "make_strata"
      ]
    },
    {
      "page": "plot_prediction_deviation_panels",
      "title": "Plot Prediction Deviation Panels",
      "topics": [
        "plot_prediction_deviation_panels"
      ]
    },
    {
      "page": "plot.maihda_analysis",
      "title": "Plot a MAIHDA Analysis",
      "topics": [
        "plot.maihda_analysis"
      ]
    },
    {
      "page": "plot.maihda_comparison",
      "title": "Plot a MAIHDA Model Comparison",
      "topics": [
        "plot.maihda_comparison"
      ]
    },
    {
      "page": "plot.maihda_group_comparison",
      "title": "Plot a MAIHDA Group Comparison",
      "topics": [
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      "title": "Plot MAIHDA Model Results",
      "topics": [
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      "page": "plot.maihda_ternary",
      "title": "Plot MAIHDA Ternary Diagram",
      "topics": [
        "plot.maihda_ternary"
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    {
      "page": "predict_maihda",
      "title": "Predict from MAIHDA Model",
      "topics": [
        "predict_maihda"
      ]
    },
    {
      "page": "print.maihda_analysis",
      "title": "Print a MAIHDA Analysis",
      "topics": [
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      ]
    },
    {
      "page": "print.maihda_group_comparison",
      "title": "Print method for MAIHDA group comparisons",
      "topics": [
        "print.maihda_group_comparison"
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    },
    {
      "page": "print.maihda_model",
      "title": "Print method for maihda_model",
      "topics": [
        "print.maihda_model"
      ]
    },
    {
      "page": "print.maihda_strata",
      "title": "Print method for maihda_strata objects",
      "topics": [
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    {
      "page": "print.maihda_summary",
      "title": "Print method for maihda_summary objects",
      "topics": [
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    {
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        "Introduction",
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        "Real-World Example Analysis",
        "Step 1 & 2: Create Intersectional Strata and Fit a Null MAIHDA Model",
        "Step 3: Evaluate Proportional Change in Variance (PCV)",
        "Step 4: Stepwise PCV Decomposition",
        "Step 5: Visualizations",
        "Step 6: Compare Intersectional Inequality Across Groups",
        "Where to next",
        "Interactive Shiny App",
        "References"
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        "Discriminatory accuracy (AUC / C-statistic)",
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