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Set and query the ego sampling design

Source: R/ego.design.R
ego_design.Rd

Extract, set, remove, or update the survey design associated with an ego-centered dataset.

Usage

ego_design(x, ...)

# S3 method for class 'egor'
ego_design(x, ...)

# S3 method for class 'nested_egor'
ego_design(x, ...)

ego_design(x, ...) <- value

# S3 method for class 'egor'
ego_design(x, ...) <- value

# S3 method for class 'nested_egor'
ego_design(x, ...) <- value

has_ego_design(x)

# S3 method for class 'egor'
has_ego_design(x)

# S3 method for class 'nested_egor'
has_ego_design(x)

strip_ego_design(x)

Arguments

x

an egor object.

...

arguments to be passed to methods

value

A list of arguments to srvyr::as_survey_design() specifying the sampling design for the egos in terms of the ego variables. Variable names can be referenced as strings, as one-sided formulas, or using dplyr::select() syntax. It is recommended to use alist() rather than list() to construct this argument, particularly when using the select() syntax. Pass NULL to set no design.

Note

This can be useful for adjusting or re-initializing the ego design information after the underlying ego attributes had been modified.

Examples

data(egor32)

ego_design(egor32)
#> Independent Sampling design (with replacement)
#> Called via srvyr
#> Data variables: 
#>   - .egoID (dbl), sex (fct), age (fct), age.years (int), country (chr), income
#>     (dbl)

ego_design(egor32) <- alist(strata = sex)

ego_design(egor32)
#> Stratified Independent Sampling design (with replacement)
#> Called via srvyr
#> Sampling variables:
#>   - ids: `1` 
#>   - strata: sex 
#> Data variables: 
#>   - .egoID (dbl), sex (fct), age (fct), age.years (int), country (chr), income
#>     (dbl)