tests/testthat/test_binomtest.r

In poolr: Methods for Pooling P-Values from (Dependent) Tests

### library(poolr); library(testthat); Sys.setenv(NOT_CRAN="true")

source("tolerances.r")

context("Checking binomtest() function")

test_that("binomtest() works correctly under independence.", {

  res <- binomtest(grid2ip.p)
  out <- capture.output(print(res))

  expect_equivalent(c(res$p), 3.763872e-09, tolerance = p_tol)
  expect_equivalent(c(res$statistic), 11, tolerance = stat_tol)

})

test_that("binomtest() works correctly with effective number of tests.", {

  res_nyh <- binomtest(grid2ip.p, adjust = "nyholt", R = mvnconv(grid2ip.ld, target = "p", cov2cor = TRUE))
  res_lj  <- binomtest(grid2ip.p, adjust = "liji", R = mvnconv(grid2ip.ld, target = "p", cov2cor = TRUE))
  res_gao <- binomtest(grid2ip.p, adjust = "gao", R = mvnconv(grid2ip.ld, target = "p", cov2cor = TRUE))
  res_gal <- binomtest(grid2ip.p, adjust = "galwey", R = mvnconv(grid2ip.ld, target = "p", cov2cor = TRUE))
  res_user <- binomtest(grid2ip.p, m = 18)

  out <- capture.output(print(res_nyh))
  out <- capture.output(print(res_lj))
  out <- capture.output(print(res_gao))
  out <- capture.output(print(res_gal))
  out <- capture.output(print(res_user))

  expect_equivalent(c(res_nyh$p), 2.057712e-09, tolerance = p_tol)
  expect_equivalent(c(res_nyh$statistic), 11, tolerance = stat_tol)

  expect_equivalent(c(res_lj$p), 2.067037e-08, tolerance = p_tol)
  expect_equivalent(c(res_lj$statistic), 11, tolerance = stat_tol)

  expect_equivalent(c(res_gao$p), 3.763872e-09, tolerance = p_tol)
  expect_equivalent(c(res_gao$statistic), 11, tolerance = stat_tol)

  expect_equivalent(c(res_gal$p), 1.134072e-08, tolerance = p_tol)
  expect_equivalent(c(res_gal$statistic), 11, tolerance = stat_tol)

  expect_equivalent(c(res_user$p), 6.279596e-08, tolerance = p_tol)
  expect_equivalent(c(res_user$statistic), 11, tolerance = stat_tol)

})

test_that("binomtest() works correctly with empirically-derived null distributions.", {

  set.seed(1234)
  res <- binomtest(grid2ip.p, adjust = "empirical", R = grid2ip.ld)
  out <- capture.output(print(res))

  expect_equivalent(c(res$p), 0.00059994, tolerance = p_tol * emp_sca)
  expect_equivalent(c(res$statistic), 11, tolerance = stat_tol * emp_sca)
  expect_equivalent(c(res$ci[1]), 0.0002201982, tolerance = p_tol * emp_sca)
  expect_equivalent(c(res$ci[2]), 0.001305356, tolerance = p_tol * emp_sca)

  set.seed(1234)
  res <- binomtest(grid2ip.p, adjust = "empirical", R = grid2ip.ld, size = 100000)
  out <- capture.output(print(res))

  expect_equivalent(c(res$p), 0.0005099949, tolerance = p_tol * emp_sca)
  expect_equivalent(c(res$statistic), 11, tolerance = stat_tol * emp_sca)
  expect_equivalent(c(res$ci[1]), 0.0003797475, tolerance = p_tol * emp_sca)
  expect_equivalent(c(res$ci[2]), 0.0006704953, tolerance = p_tol * emp_sca)

  set.seed(1234)
  res <- binomtest(grid2ip.p, adjust = "empirical", R = grid2ip.ld, size = 1000000, batchsize = 1000)
  out <- capture.output(print(res))

  expect_equivalent(c(res$p), 0.0004199996, tolerance = p_tol * emp_sca)
  expect_equivalent(c(res$statistic), 11, tolerance = stat_tol * emp_sca)
  expect_equivalent(c(res$ci[1]), 0.000380795, tolerance = p_tol * emp_sca)
  expect_equivalent(c(res$ci[2]), 0.0004621435, tolerance = p_tol * emp_sca)

  set.seed(1234)
  res <- binomtest(grid2ip.p, adjust = "empirical", R = grid2ip.ld, size = c(1000, 10000, 100000), threshold = c(0.10, 0.01))
  out <- capture.output(print(res))

  expect_equivalent(c(res$p), 0.0005099949, tolerance = p_tol * emp_sca)
  expect_equivalent(c(res$statistic), 11, tolerance = stat_tol * emp_sca)
  expect_equivalent(c(res$ci[1]), 0.0003797475, tolerance = p_tol * emp_sca)
  expect_equivalent(c(res$ci[2]), 0.0006704953, tolerance = p_tol * emp_sca)

})