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Cluster Random Sampling

Source: R/cluster_rs.R
cluster_rs.Rd

cluster_rs draws whole groups of units (clusters) into the sample, so that either every unit in a cluster is sampled or none of them is. Use it when the sampling frame lists groups rather than individuals, for example when villages are drawn and then everyone in the drawn villages is interviewed. Because units come in whole clusters, the effective sample size is closer to the number of clusters than to the number of units.

Usage

cluster_rs(
  clusters = NULL,
  n = NULL,
  n_unit = NULL,
  prob = NULL,
  prob_unit = NULL,
  simple = FALSE,
  check_inputs = TRUE
)

Arguments

clusters

A vector of length N indicating which cluster each unit belongs to. (required)

n

Use for a design in which exactly n clusters are sampled. (optional)

n_unit

unique(n_unit) will be passed to n; must be the same for all units and of length N. (optional)

prob

Use for a design in which either floor(N_clusters*prob) or ceiling(N_clusters*prob) clusters are sampled. Which of the two is used is itself random: the ceiling is drawn with probability equal to the fractional part of N_clusters*prob and the floor otherwise, which makes each cluster's probability of inclusion exactly prob. Must be a real number between 0 and 1 inclusive. (optional)

prob_unit

unique(prob_unit) will be passed to prob; must be the same for all units and of length N. (optional)

simple

Logical, defaults to FALSE. If TRUE, clusters are drawn independently (simple random sampling of clusters), so the number of sampled clusters varies from draw to draw. Do not specify n when simple = TRUE. (optional)

check_inputs

Logical. Whether to verify before sampling that the arguments are internally consistent: that n does not exceed the number of clusters, that probabilities lie between 0 and 1, and so on. Defaults to TRUE. Set to FALSE to skip the checks when drawing many samples from arguments that have already been verified; declaring the design once with declare_rs() and drawing from it with draw_rs() does this for you. (optional)

Value

A numeric vector of length N indicating whether each unit is sampled (1) or not (0). Every unit in a cluster receives the same value.

Details

By default the clusters are drawn by complete random sampling, so a fixed number of clusters is sampled on every draw. Setting simple = TRUE draws each cluster independently instead, using simple_rs().

See also

complete_rs(), strata_and_cluster_rs(), cluster_ra(), cluster_rs_probabilities()

Examples

# Ten clusters, of sizes 1 through 10
clusters <- rep(letters[1:10], times = 1:10)

S <- cluster_rs(clusters = clusters)
table(S, clusters)
#>    clusters
#> S    a  b  c  d  e  f  g  h  i  j
#>   0  0  2  0  0  5  0  7  8  9  0
#>   1  1  0  3  4  0  6  0  0  0 10

S <- cluster_rs(clusters = clusters, n = 4)
table(S, clusters)
#>    clusters
#> S    a  b  c  d  e  f  g  h  i  j
#>   0  0  2  0  4  5  6  7  0  9  0
#>   1  1  0  3  0  0  0  0  8  0 10

# Each cluster drawn independently, so the number sampled varies
S <- cluster_rs(clusters = clusters, prob = 0.4, simple = TRUE)
table(S, clusters)
#>    clusters
#> S    a  b  c  d  e  f  g  h  i  j
#>   0  1  2  3  4  5  0  7  0  9 10
#>   1  0  0  0  0  0  6  0  8  0  0