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Precision for a Constrained Allocation

Source: R/n_alloc.R
prec_alloc.Rd

Compute aggregate precision for a stratum allocation.

Usage

prec_alloc(frame, ...)

# Default S3 method
prec_alloc(
  frame,
  n,
  ...,
  domains = NULL,
  alpha = 0.05,
  deff = 1,
  resp_rate = 1,
  unit_cost = NULL,
  plan = NULL
)

# S3 method for class 'svyplan_n'
prec_alloc(frame, ...)

Arguments

frame

For the default method: a stratum-level data frame in the same format as the frame argument to n_alloc() (one row per stratum, with at least N and sd or var columns). See n_alloc() for the full column reference). For svyplan_n objects: an allocation result from n_alloc().

...

Additional arguments passed to methods. Unused arguments are rejected.

n

Stratum sample sizes, length nrow(frame) (default method only).

domains

Character vector of column names in frame to treat as domain identifiers, or NULL (default) for no domains.

alpha

Significance level, default 0.05.

deff

Design effect multiplier (> 0).

resp_rate

Expected response rate, in (0, 1]. Default 1.

unit_cost

Optional scalar or length-nrow(frame) vector of per-stratum unit costs, overriding frame$unit_cost.

plan

Optional svyplan() object providing design defaults.

Value

A svyplan_prec object with type = "alloc".

See also

n_alloc().

Examples

frame <- data.frame(
  N    = c(4000, 3000, 3000),
  sd   = c(10, 15, 8),
  mean = c(50, 60, 55)
)
res <- n_alloc(frame, n = 600)
prec_alloc(res)
#> Sampling precision for alloc
#> n = 221 n = 248 n = 133
#> se = 0.4305, moe = 0.8438, cv = 0.0079