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Inclusion Probabilities: Cluster Sampling

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 that indicates which cluster each unit belongs to.

n

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

n_unit

unique(n_unit) will be passed to n. Must be the same for all units (optional)

prob

Use for a design in which either floor(N_clusters*prob) or ceiling(N_clusters*prob) clusters are sampled. The probability of being sampled is exactly prob because with probability 1-prob, floor(N_clusters*prob) clusters will be sampled and with probability prob, ceiling(N_clusters*prob) clusters will be sampled. prob must be a real number between 0 and 1 inclusive. (optional)

prob_unit

unique(prob_unit) will be passed to the prob argument and must be the same for all units.

simple

logical, defaults to FALSE. If TRUE, simple random sampling of clusters. When simple = TRUE, please do not specify n.

check_inputs

logical. Defaults to TRUE.

Value

A vector length N indicating the probability of being sampled.

Examples


# Two Group Designs
clusters <- rep(letters, times = 1:26)
probs <- cluster_rs_probabilities(clusters = clusters)
table(probs, clusters)
#>      clusters
#> probs  a  b  c  d  e  f  g  h  i  j  k  l  m  n  o  p  q  r  s  t  u  v  w  x
#>   0.5  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
#>      clusters
#> probs  y  z
#>   0.5 25 26

prob_mat <- cluster_rs_probabilities(clusters = clusters, n = 10)
table(probs, clusters)
#>      clusters
#> probs  a  b  c  d  e  f  g  h  i  j  k  l  m  n  o  p  q  r  s  t  u  v  w  x
#>   0.5  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
#>      clusters
#> probs  y  z
#>   0.5 25 26

prob_mat <- cluster_rs_probabilities(clusters = clusters, prob = .3)
table(probs, clusters)
#>      clusters
#> probs  a  b  c  d  e  f  g  h  i  j  k  l  m  n  o  p  q  r  s  t  u  v  w  x
#>   0.5  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
#>      clusters
#> probs  y  z
#>   0.5 25 26