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.
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