cluster_rs implements a random sampling procedure in which groups of units are sampled together (as a cluster). This function conducts complete random sampling at the cluster level, unless simple = TRUE, in which case simple_rs analogues are used.
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 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.
Examples
clusters <- rep(letters, times=1:26)
S <- cluster_rs(clusters = clusters)
table(S, clusters)
#> clusters
#> S a b c d e f g h i j k l m n o p q r s t u v w x y
#> 0 0 0 3 4 0 6 7 0 9 0 11 12 0 0 15 0 0 18 19 20 0 0 0 0 25
#> 1 1 2 0 0 5 0 0 8 0 10 0 0 13 14 0 16 17 0 0 0 21 22 23 24 0
#> clusters
#> S z
#> 0 26
#> 1 0
S <- cluster_rs(clusters = clusters, n = 13)
table(S, clusters)
#> clusters
#> S a b c d e f g h i j k l m n o p q r s t u v w x y
#> 0 1 0 3 4 5 0 7 8 9 0 0 12 0 14 0 16 0 18 0 0 21 0 23 0 0
#> 1 0 2 0 0 0 6 0 0 0 10 11 0 13 0 15 0 17 0 19 20 0 22 0 24 25
#> clusters
#> S z
#> 0 0
#> 1 26