Replicate Weights Survey Design

A survey design object using replicate weights for variance estimation. Create with as_survey_replicate().

Usage

survey_replicate(
  data = data.frame(),
  metadata = survey_metadata(),
  variables = list(),
  groups = character(0),
  call = NULL,
  calibration = NULL
)

Arguments

data: A data.frame containing the survey data. Prefer as_survey_replicate() over calling this constructor directly.
metadata: A survey_metadata object. Created automatically by as_survey_replicate().
variables: A named list of design specification (weights, repweights, type, scale, rscales, fpc, fpctype, fpc_applied, fpc_fraction, mse, rho). Set automatically by as_survey_replicate().
groups: Set by surveytidy's group_by(). Always character(0) in standalone surveycore use.
call: Language object capturing the construction call.
calibration: A list of calibration data elements produced by as_caldata(), or NULL (default) for no calibration. When non-NULL, variance estimation routines apply a Deville-Sarndal calibration correction.

Value

A survey_replicate object.

Design variables (`@variables`)

weights: Character string naming the weight column.
repweights: Character vector of replicate weight column names. The replicate weight matrix is computed on demand from design@data[, design@variables$repweights] — it is not stored as a property.
type: Replicate weight method: one of "JK1", "JK2", "JKn", "BRR", "Fay", "bootstrap", "ACS", "successive-difference", or "other".
scale: Numeric scaling factor for variance estimation.
rscales: Numeric vector of replicate-specific scales, or NULL.
fpc: Name of the FPC column the design was built from, or NULL. Provenance only: no replicate variance formula reads it.
fpctype: "fraction" or "correction": how to read the fpc column.
fpc_applied: Where the finite population correction reached the variance: "rscales" (inside rscales), "repweights" (inside the replicate weight columns), "none" (an FPC was available and was not applied), or NULL (no FPC was available, or the design predates this key). With fpc set and fpc_applied NULL, whether the FPC was applied is not recorded.
fpc_fraction: The sampling fraction f per replicate, a numeric vector with one value per replicate column, when as_survey_replicate() applied a numeric fpc; otherwise NULL.
mse: Logical. Use MSE estimates?
rho: Fay shrinkage factor for type = "Fay"; NULL for every other type.

References

Canty, A.J. and Davison, A.C. (1999) Resampling-based variance estimation for labour force surveys. The Statistician 48(3), 379–391.

Deville, J.-C. and Sarndal, C.-E. (1992) Calibration estimators in survey sampling. Journal of the American Statistical Association 87(418), 376–382.

Deville, J.-C., Sarndal, C.-E. and Sautory, O. (1993) Generalized raking procedures in survey sampling. Journal of the American Statistical Association 88(423), 1013–1020.

Judkins, D.R. (1990) Fay's method for variance estimation. Journal of Official Statistics 6(3), 223–239.

Rao, J.N.K., Wu, C.F.J. and Yue, K. (1992) Some recent work on resampling methods for complex surveys. Survey Methodology 18(2), 209–217.

Shao, J. and Tu, D. (1995) The Jackknife and Bootstrap. Springer.

Examples

# Prefer as_survey_replicate() over calling survey_replicate() directly
set.seed(1)
df <- data.frame(
  y = rnorm(20),
  wt = runif(20, 1, 3),
  rep1 = runif(20, 0.5, 2),
  rep2 = runif(20, 0.5, 2)
)
d <- as_survey_replicate(
  df,
  weights = wt,
  repweights = starts_with("rep"),
  type = "BRR"
)
class(d)
#> [1] "surveycore::survey_replicate" "surveycore::survey_base"     
#> [3] "S7_object"