Create a Replicate Weights Survey Design

Creates a survey design object using replicate weights for variance estimation. Supports all common replicate methods: jackknife (JK1, JK2, JKn), balanced repeated replication (BRR, Fay), bootstrap, ACS, successive-difference, and user-defined types. Uses a tidy-select interface for weight and replicate-weight columns.

Usage

as_survey_rep(
  data,
  weights,
  repweights,
  type = c("JK1", "JK2", "JKn", "BRR", "Fay", "bootstrap", "ACS",
    "successive-difference", "other"),
  scale = NULL,
  rscales = NULL,
  fpc = NULL,
  fpctype = c("fraction", "correction"),
  mse = TRUE
)

Arguments

data

A data.frame containing the survey responses. Must have at least one row and unique column names.

weights

<tidy-select> Sampling weight column (a single column, values strictly > 0). Required.

repweights

<tidy-select> Replicate weight columns. Must select at least one column. Supports tidy-select helpers (e.g., starts_with("repwt")). Required.

type

Character. Replicate weight method. One of "JK1" (delete-1 jackknife), "JK2" (delete-1 jackknife, stratified), "JKn" (delete-1 jackknife with varying replication counts), "BRR" (balanced repeated replication), "Fay" (Fay's method, a modified BRR), "bootstrap", "ACS" (used in American Community Survey), "successive-difference", or "other" (user-specified scale).

scale

Numeric. Scaling factor applied to the replicate variance formula. If NULL (default), computed automatically from type and the number of replicates: (R-1)/R for jackknife methods, 1/4 for BRR/Fay, 1/R for bootstrap/ACS, 2/R for successive-difference, 1 for other.

rscales

Numeric vector of replicate-specific scaling factors, or NULL. If provided, must have the same length as the number of replicate weight columns selected by repweights.

fpc

<tidy-select> Finite population correction column (a single column). Used by some replicate methods to adjust the variance estimator. NULL means no FPC correction.

fpctype

Character. How fpc is interpreted: "fraction" (sampling fraction, 0–1) or "correction" (multiplier for the replicate variance). Default "fraction".

mse

Logical. If TRUE (default), use mean-squared-error estimates (subtract the full-sample estimate rather than the mean replicate estimate when computing variance). Recommended for most designs.

Value

A survey_replicate object.

Tidy-select

Both weights and repweights support tidy-select syntax:

# Bare name for weights
as_survey_rep(df, weights = wt, repweights = starts_with("repwt"), type = "BRR")
# c() for explicit replicate columns
as_survey_rep(df, weights = wt, repweights = c(rep1, rep2, rep3), type = "JK1")

Replicate weight matrix

The replicate weight matrix is not stored in the object. Only the column names are stored in @variables$repweights. Variance estimation computes the matrix on demand: as.matrix(design@data[, design@variables$repweights]).

Memory usage

Each call to an estimation function (e.g., get_means(), get_totals()) materialises the full replicate weight matrix from the data frame. For large designs (e.g., ACS PUMS with 500k+ rows × 80 replicates), this is roughly nrow * n_replicates * 8 bytes per call (~363 MB for ACS Wyoming × 80). If you are estimating many variables, this is repeated for each call. This behaviour matches the survey package reference implementation.

See also

as_survey() for Taylor series designs, as_survey_twophase() for two-phase designs, set_var_label(), set_variable_labels() to add variable metadata

Other constructors: as_survey(), as_survey_calibrated(), as_survey_srs(), as_survey_twophase(), survey_calibrated(), survey_data(), survey_replicate(), survey_srs(), survey_taylor(), survey_twophase()

Examples

# ACS PUMS Wyoming: 80 successive-difference replicate weights
d_acs <- as_survey_rep(
  acs_pums_wy,
  weights    = pwgtp,
  repweights = pwgtp1:pwgtp80,
  type       = "successive-difference"
)

# Explicit replicate columns using c()
d_sub <- as_survey_rep(
  acs_pums_wy,
  weights    = pwgtp,
  repweights = c(pwgtp1, pwgtp2, pwgtp3, pwgtp4),
  type       = "JK1"
)