{
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  "Package": "weightflow",
  "Title": "Declarative API for Staged Survey Weights",
  "Version": "0.1.0",
  "Authors@R": "person(\"Juan Pablo\", \"Ferreira\", email = \"juanpablo.ferreira@fcea.edu.uy\", role = c(\"aut\", \"cre\"))",
  "Description": "Builds survey weights from design base weights by chaining\nhierarchical adjustments (unknown eligibility, nonresponse and\ncalibration) through a declarative, pipeable,\n'tidymodels'-style API. Calibration follows Deville and Sarndal\n(1992) <doi:10.2307/2290268>. Variances are obtained with a\nbootstrap that resamples primary sampling units and re-applies\nthe whole recipe on each replicate, following the rescaling\nbootstrap of Rao and Wu (1988)\n<doi:10.1080/01621459.1988.10478591>, so the replicate weights\ncarry the variability of every adjustment. The weights also\nbridge to the 'survey' and 'srvyr' packages for design-based\ninference.",
  "License": "MIT + file LICENSE",
  "Encoding": "UTF-8",
  "Language": "en-US",
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  "URL": "https://github.com/jpferreira33/weightflow,\nhttps://jpferreira33.github.io/weightflow/",
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  "Maintainer": "Juan Pablo Ferreira <juanpablo.ferreira@fcea.edu.uy>",
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    "step_trim",
    "step_trim_weights",
    "step_unknown_eligibility",
    "weight_factors",
    "weighting_spec",
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      "title": "Example target population for weightflow",
      "object": "population",
      "class": [
        "data.frame"
      ],
      "fields": [
        "person_id",
        "household_id",
        "psu",
        "region",
        "sex",
        "age",
        "income",
        "employed"
      ],
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      "table": true,
      "tojson": true
    },
    {
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      "title": "Example survey sample (select-one-person, multistage)",
      "object": "sample_one",
      "class": [
        "data.frame"
      ],
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        "person_id",
        "household_id",
        "psu",
        "region",
        "sex",
        "age",
        "pw",
        "status",
        "unknown_elig",
        "ineligible",
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        "responded",
        "n_elig",
        "p_within",
        "income",
        "employed"
      ],
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      "table": true,
      "tojson": true
    },
    {
      "name": "sample_survey",
      "title": "Example survey sample (take-all roster)",
      "object": "sample_survey",
      "class": [
        "data.frame"
      ],
      "fields": [
        "person_id",
        "household_id",
        "psu",
        "region",
        "sex",
        "age",
        "pw",
        "unknown_elig",
        "responded",
        "income",
        "employed"
      ],
      "rows": 467,
      "table": true,
      "tojson": true
    }
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    {
      "page": "as_svydesign",
      "title": "Export weightflow weights to a survey design",
      "topics": [
        "as_svrepdesign",
        "as_svydesign"
      ]
    },
    {
      "page": "bootstrap_estimate",
      "title": "Bootstrap estimate, standard error and confidence interval",
      "topics": [
        "bootstrap_estimate",
        "boot_mean",
        "boot_total"
      ]
    },
    {
      "page": "bootstrap_weights",
      "title": "Bootstrap replicate weights that re-apply the recipe",
      "topics": [
        "bootstrap_weights"
      ]
    },
    {
      "page": "collect_replicate_weights",
      "title": "Collect replicate weights into a data frame ready for srvyr",
      "topics": [
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      ]
    },
    {
      "page": "collect_weights",
      "title": "Extract the data with the computed weights",
      "topics": [
        "collect_weights"
      ]
    },
    {
      "page": "design_effect",
      "title": "Kish design effect from unequal weighting",
      "topics": [
        "design_effect"
      ]
    },
    {
      "page": "plot.prepped_weighting_spec",
      "title": "Diagnostic plots for the weights",
      "topics": [
        "plot.prepped_weighting_spec"
      ]
    },
    {
      "page": "population",
      "title": "Example target population for weightflow",
      "topics": [
        "population"
      ]
    },
    {
      "page": "prep",
      "title": "Estimate the weighting cascade",
      "topics": [
        "prep"
      ]
    },
    {
      "page": "report_weighting",
      "title": "Build a nice HTML report of the weighting recipe",
      "topics": [
        "report_weighting"
      ]
    },
    {
      "page": "sample_one",
      "title": "Example survey sample (select-one-person, multistage)",
      "topics": [
        "sample_one"
      ]
    },
    {
      "page": "sample_survey",
      "title": "Example survey sample (take-all roster)",
      "topics": [
        "sample_survey"
      ]
    },
    {
      "page": "step_assert",
      "title": "Assert conditions on the weights at this point of the cascade",
      "topics": [
        "step_assert"
      ]
    },
    {
      "page": "step_calibrate",
      "title": "Calibration to population totals",
      "topics": [
        "step_calibrate"
      ]
    },
    {
      "page": "step_drop_ineligible",
      "title": "Drop ineligible (out-of-scope) units",
      "topics": [
        "step_drop_ineligible"
      ]
    },
    {
      "page": "step_model_calibration",
      "title": "Model calibration (model-assisted, Wu & Sitter 2001)",
      "topics": [
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    },
    {
      "page": "step_nonresponse",
      "title": "Nonresponse adjustment",
      "topics": [
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    },
    {
      "page": "step_rescale",
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      "topics": [
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      ]
    },
    {
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      "title": "Round the final weights",
      "topics": [
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      ]
    },
    {
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      "title": "Within-household selection adjustment",
      "topics": [
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    },
    {
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      "title": "Trim extreme weights",
      "topics": [
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      ]
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      "title": "Automatic weight trimming (survey-style)",
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      "topics": [
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      "page": "summary.prepped_weighting_spec",
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    },
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      "page": "weight_factors",
      "title": "Per-unit adjustment factors table",
      "topics": [
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    {
      "page": "weighting_spec",
      "title": "Start a weighting specification",
      "topics": [
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    {
      "page": "y_model",
      "title": "Specify a working model for a study variable y",
      "topics": [
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      ]
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  "_rundeps": [],
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      "filename": "variance-estimation.html",
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        "Method 1: a PSU bootstrap that re-applies the recipe",
        "Estimates with bootstrap standard errors",
        "Method 2: hand the weights to the survey package",
        "Replicate weights for a tidyverse workflow",
        "Which one to use"
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