tests/testthat/test-cluster_rs.R

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

context("Cluster Random Sampling")
clusters <- rep(letters[1:15], times = 1:15)

test_that("Two Group Designs", {
  S <- cluster_rs(clusters = clusters)
  probs <- cluster_rs_probabilities(clusters = clusters)
  expect_true(all(colSums(table(S, clusters) != 0) == 1))
  expect_true(all(probs == .5))
})

test_that("Two Gropu n = 13", {
  S <- cluster_rs(clusters = clusters, n = 13)
  probs <- cluster_rs_probabilities(clusters = clusters, n = 13)
  expect_true(all(colSums(table(S, clusters) != 0) == 1))
  expect_true(all(probs == 13 / 15))
})

test_that("prob = .5", {
  S <- cluster_rs(clusters = clusters, prob = .5)
  probs <- cluster_rs_probabilities(clusters = clusters, prob = .5)
  expect_true(all(colSums(table(S, clusters) != 0) == 1))
  expect_true(all(probs == .5))
})

test_that("prob = 0", {
  S <- cluster_rs(clusters = clusters, prob = 0)
  probs <- cluster_rs_probabilities(clusters = clusters, prob = 0)
  expect_true(all(S == 0))
  expect_true(all(probs == 0))
})

test_that("prob = 1", {
  S <- cluster_rs(clusters = clusters, prob = 1)
  probs <- cluster_rs_probabilities(clusters = clusters, prob = 1)
  expect_true(all(S == 1))
  expect_true(all(probs == 1))
})

test_that("clust simple ", {
  clusters <- gl(10, 2)
  S <- cluster_rs(clusters = clusters, simple = TRUE)
  s_prob <-
    cluster_rs_probabilities(clusters = clusters, simple = TRUE)
  expect_true(all(rowSums(table(clusters, S) > 0) == 1))
  expect_true(all(s_prob > 0 & s_prob < 1))
})

test_that("n and simple is error", {
  expect_error(cluster_rs(
    clusters = gl(10, 2),
    simple = TRUE,
    n = 3
  ))
  expect_error(cluster_rs_probabilities(
    clusters = gl(10, 2),
    simple = TRUE,
    n = 3
  ))
})



test_that("_unit",{
  clusters <- rep(c("A", "B", "C"), c(2, 2, 2))
  cluster_rs(clusters = clusters, n_unit = rep(1, 6))
  expect_error(cluster_ra(clusters = clusters, m_unit = 1:6))
  cluster_ra(clusters = clusters, prob_unit = rep(0.5, 6))
  expect_error(cluster_ra(clusters = clusters, prob_unit = seq(0.1, 0.6, by = 0.1)))
})