Within-household selection adjustment — step_select

When one (or a subsample) of the units is selected within each cluster, the selected unit represents all eligible units in the cluster, so the weight is multiplied by the inverse of the within-cluster selection probability. Apply it after the (cluster-level) eligibility adjustment and before the nonresponse adjustment.

Usage

step_select_within(spec, prob = NULL, n_eligible = NULL, n_selected = NULL)

Arguments

spec: a weighting_spec.
prob: unquoted column with the within-household selection probability of the selected person (need not be 1/n_eligible). The weight is multiplied by 1/prob.
n_eligible: unquoted column with the number of eligible persons in the household, for simple random selection within the household. When a single person is selected (the default), the weight is multiplied by n_eligible (equivalent to prob = 1/n_eligible).
n_selected: optional number of persons selected per household under simple random selection, when more than one person is subsampled. Either a single number (same subsample size in every household) or an unquoted column (subsample size varying by household). The weight is multiplied by n_eligible / n_selected (equivalent to prob = n_selected/n_eligible). Defaults to 1. Only used together with n_eligible.

Value

The input weighting_spec with this step appended to its recipe. The step is recorded only; it is evaluated when prep() is called.

Details

Despite the name, the cluster need not be a household and the unit need not be a person: the step is the generic within-cluster subsampling adjustment. In a multi-stage design it can appear more than once – e.g. dwellings selected within sampled area segments, then persons selected within dwellings – each occurrence undoing one stage of subsampling.

Examples

# simple random selection of one eligible person per household
df <- transform(sample_survey,
                n_elig = ave(person_id, household_id, FUN = length))
weighting_spec(df, base_weights = pw) |>
  step_select_within(n_eligible = n_elig)
#> 
#> == Weighting specification (weightflow) ==
#> Data    : 467 cases
#> Base wts: pw
#> Steps   :
#>   1. within-household selection
#> Status  : not estimated
#> 

# simple random selection of two eligible persons per household
weighting_spec(df, base_weights = pw) |>
  step_select_within(n_eligible = n_elig, n_selected = 2)
#> 
#> == Weighting specification (weightflow) ==
#> Data    : 467 cases
#> Base wts: pw
#> Steps   :
#>   1. within-household selection
#> Status  : not estimated
#>