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Inclusion probabilities: Cluster Sampling

Source: R/cluster_rs.R
cluster_rs_probabilities.Rd

Returns each unit's probability of being sampled when whole clusters are drawn. Every unit in a cluster shares its cluster's probability.

Usage

cluster_rs_probabilities(
  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 giving each unit's probability of being included in the sample. Every unit in a cluster shares one probability.

Details

These are the quantities inverse-probability weights are built from: weight each sampled unit by the reciprocal of its inclusion probability, which obtain_inclusion_probabilities() extracts for you.

See also

cluster_rs()

Examples


clusters <- rep(letters[1:10], times = 1:10)

probs <- cluster_rs_probabilities(clusters = clusters)
table(probs, clusters)
#>      clusters
#> probs  a  b  c  d  e  f  g  h  i  j
#>   0.5  1  2  3  4  5  6  7  8  9 10

probs <- cluster_rs_probabilities(clusters = clusters, n = 4)
table(probs, clusters)
#>      clusters
#> probs  a  b  c  d  e  f  g  h  i  j
#>   0.4  1  2  3  4  5  6  7  8  9 10

probs <- cluster_rs_probabilities(clusters = clusters, prob = 0.3)
table(probs, clusters)
#>      clusters
#> probs  a  b  c  d  e  f  g  h  i  j
#>   0.3  1  2  3  4  5  6  7  8  9 10