# cluster_rs: Cluster Random Sampling In DeclareDesign/randomizr: Easy-to-Use Tools for Common Forms of Random Assignment and Sampling

## Description

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

 ```1 2``` ```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.

## Value

A numeric vector of length N that indicates if a unit is sampled (1) or not (0).

## Examples

 ```1 2 3 4 5 6 7``` ```clusters <- rep(letters, times=1:26) S <- cluster_rs(clusters = clusters) table(S, clusters) S <- cluster_rs(clusters = clusters, n = 13) table(S, clusters) ```

DeclareDesign/randomizr documentation built on June 2, 2019, 3:50 p.m.