optsize {surveyplanning}

Optimal sample size allocation

Description

The function computes optimal sample size allocation over strata.

Usage

optsize(
  H,
  n,
  poph,
  s2h = NULL,
  Rh = NULL,
  deffh = NULL,
  fullsampleh = NULL,
  dataset = NULL
)

Arguments

H

The stratum variable. One dimensional object convertible to one-column data.table, variable name as character, or column number.

n

Total sample size. One dimensional object with length one.

poph

Population size in each stratum. One dimensional object convertible to one-column data.table, variable name as character, or column number.

s2h

The expected population variance S^2 for variables of interest in each stratum (optional). If not defined, it is assumed to be 1 in each stratum. Object convertible to data.table, variable name as character vector, or column numbers.

Rh

The expected response rate in each stratum (optional). If not defined, it is assumed to be 1 in each stratum (full-response). Object convertible to one-column data.table, variable name as character, or column number.

deffh

The expected design effect for the estimate of variable (optional). If not defined, it is assumed to be 1 for each variable in each stratum. If is defined, then variables is defined the same arrangement as Yh. Object convertible to data.table, variable name as character vector, or column numbers.

fullsampleh

Variable for detection fully surveyed stratum (optinal). If not defined, it is assumed to be 1 in each stratum (full-response). Object convertible to one-column data.table, variable name as character, or column number.

dataset

Optional survey data object convertible to data.table with one row for each stratum.

Value

An object as data.table, with variables:
H - stratum,
variable - the name of variable for population variance S^2,
s2h - population variance S^2,
Rh - the expectedresponse rate,
deffh - the expected design effect,
poph - population size,
deffh - design effect,
fullsampleh - full sample indicator,
nh - sample size.

Details

If s2h and Rh is not defined, the sample allocation will be calculated as proportional allocation (proportional to the population size). If Rh is not defined, the sample allocation will be calculated as Neyman allocation.

See Also

expsize, dom_optimal_allocation

Examples

library("data.table")
data <- data.table(H = 1 : 3,
                   s2h=10 * runif(3),
                   s2h2 = 10 * runif(3),
                   poph = 8 * 1 : 3,
                   Rh = rep(1, 3),
                   dd = c(1, 1, 1))

vars <- optsize(H = "H",
                s2h = c("s2h", "s2h2"),
                n = 10, poph = "poph",
                Rh = "Rh",
                fullsampleh = NULL,
                dataset = data)
vars