tests/testthat/test-plot.findn.R

In findn: Simulation Based Sample Size Estimation

test_that("plot.findn works", {
  set.seed(20210520)
  fun_ttest1 <- function(n, k) {
    n_mat <- matrix(rnorm(n * k, mean = 5, sd = 10), ncol = k)
    pvals <- apply(n_mat, 2, function(x) t.test(x)$p.value)
    mean(pvals <= 0.05)
  }
  
  fun_ttest2 <- function(n, k) {
    n_mat <- matrix(rnorm(n * k, mean = 5, sd = 2.5), ncol = k)
    pvals <- apply(n_mat, 2, function(x) t.test(x)$p.value)
    mean(pvals <= 0.05)
  }
  
  res_bll1 <- suppressWarnings(findn(fun = fun_ttest1, targ = 0.8, start = 100))
  plot_bll1 <- plot(res_bll1, min_n = 1, power_lim = 0.95)
  plot_bll2 <- plot(res_bll1, min_n = 1, max_n = 100)
  res_bll2 <- suppressWarnings(findn(fun = fun_ttest2, targ = 0.8, start = 100,
    max_evals = 3000))
  plot_bll3 <- plot(res_bll2)
  
  expect_s3_class(plot_bll1, "ggplot")
  expect_gt(max(plot_bll1$data$Lower.CL), 0.95)
  expect_true(all(plot_bll1$data$Upper.CL[which(
    plot_bll1$data$Rating == "Too Low")] < 0.8))
  expect_true(all(plot_bll1$data$Lower.CL[which(
    plot_bll1$data$Rating == "Sufficient")] > 0.8))
  expect_equal(max(plot_bll2$data$n), 100)
  expect_equal(min(plot_bll2$data$n), 1)
  expect_equal(sum(plot_bll3$data$Rating == "Uncertain"), 0)
})