cluster_rs_probabilities: Inclusion probabilities: Cluster Sampling

Description

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
)

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.

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)

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.

Examples

Run this code


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

probs <- cluster_rs_probabilities(clusters = clusters)
table(probs, clusters)

probs <- cluster_rs_probabilities(clusters = clusters, n = 4)
table(probs, clusters)

probs <- cluster_rs_probabilities(clusters = clusters, prob = 0.3)
table(probs, clusters)