Hand a sample to the survey package — as

Builds a survey design object from a select_units() sample so that the estimators of that package (calibration, post-stratification, domains, ratios, regression) can be used on the field data. Units not sampled are dropped; the weights are the inverse inclusion probabilities, and the strata of the sample are the strata of the design.

Usage

as_svydesign(sample, variance = c("brewer", "srs"))

Arguments

sample: A select_units() sample.
variance: "brewer" or "srs" (ignored for replicated samples).

Value

A survey.design2 or svyrep.design object.

Details

Samples with interpenetrating replicates (method = "systematic", replicates > 1) become a replicate-weight design (survey::svrepdesign()) whose variance is the variance between the replicate estimates, the one design_variance() uses.
Other samples become a survey::svydesign(): with variance = "brewer" (default) the without-replacement probability-proportional-to- size approximation of Brewer, which needs no joint probabilities; with variance = "srs" the finite-population correction of simple random sampling within strata. Neither uses the spatial balance of the local pivotal method, so for the variance of a total of a spatially balanced sample prefer design_variance(); use the survey object for what it adds.

Examples

if (requireNamespace("survey", quietly = TRUE)) {
  cells <- expand.grid(x = 1:10, y = 1:10)
  cells$unit <- paste0("c", 1:100)
  cells$crop <- 10 + cells$x + rnorm(100)
  s <- select_units(cells, n = 20, seed = 1)
  d <- as_svydesign(s)
  survey::svytotal(~crop, d)
  design_variance(s, "crop")[, c("total", "se")]
}
#> # A tibble: 1 × 2
#>   total    se
#>   <dbl> <dbl>
#> 1 1506.  30.6