cluster_rs_probabilities: Inclusion Probabilities: Cluster Sampling

In randomizr: Easy-to-Use Tools for Common Forms of Random Assignment and Sampling

Inclusion Probabilities: Cluster Sampling

Description

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)

prob_mat <- cluster_rs_probabilities(clusters = clusters, n = 10)
table(probs, clusters)

prob_mat <- cluster_rs_probabilities(clusters = clusters, prob = .3)
table(probs, clusters)

randomizr documentation built on Aug. 10, 2023, 9:07 a.m.