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  "Package": "deltapif",
  "Title": "Estimate Potential Impact and Population Attributable Fractions\nwith Aggregated Data",
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  "Authors@R": "person(\"Rodrigo\", \"Zepeda-Tello\", , \"rzepeda17@gmail.com\", role = c(\"aut\", \"cre\"))",
  "Description": "Uses the delta-method to estimate the Potential Impact\nFraction (PIF) and the Population Attributable Fraction (PAF)\nfrom summary data. It creates point-estimates, confidence\nintervals, and estimates of the variance. Provides an extension\nto the aggregated data method in Chan, Zepeda-Tello et al\n(2025) <doi:10.1002/sim.70214>.",
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    "summary",
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    "weighted_adjusted_pif",
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        "black",
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      "topics": [
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      "page": "as_covstr",
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      "topics": [
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        "as_covstr"
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    },
    {
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      "title": "Transform an object into a data.frame",
      "topics": [
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    },
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      "topics": [
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      ]
    },
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      "topics": [
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    },
    {
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      "page": "fraction_type",
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      "topics": [
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        "Example 1: Estimating the PAF for the proportion of dementia attributable to smoking",
        "Example 2: Combining subpopulations into a total",
        "Example 3: Estimating the PIF for the proportion of dementia reduced by a 15% reduction in smoking.",
        "Example 4: A categorical population attributable fraction",
        "Example 5: Combining fractions of different risks into an ensemble",
        "Example 6: Adjusted fractions",
        "Example 7: Ensuring non-negative fractions",
        "Example 8: Computing averted and attributable cases",
        "Example 9: Computing averted cases (strictly positive)",
        "Example 10: Using Hazard Ratios (HR) and Odds Ratios (OR) instead of Relative Risks (RR)",
        "References"
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        "Usage",
        "Population Attributable Fraction (PAF)",
        "Incorporating Uncertainty",
        "Potential Impact Fraction (PIF)",
        "Attributable and averted cases",
        "Combining fractions from subpopulations",
        "Combining fractions from multiple risks",
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