test_0w_4s.R
In HRM: High-Dimensional Repeated Measures

context("0 Wholeplot, 4 Subplot")

n <- 4
l <- rep(list(1:2), n)
l <- expand.grid(l)
n <- 10

set.seed(0)
df <- data.frame(subject = gl(10,16), value = rnorm(160))
df <- cbind(df, l)

true_result <- c(1.0000000, 9.0000000, 5.11735503, 0.03546365)
result <- as.numeric(HRM::hrm_test(value~Var1*Var2*Var3*Var4, data = df, subject = "subject")$result[1, 2:5])

result_hrm <- HRM::hrm_test(value~Var1*Var2*Var3*Var4, data = df, subject = "subject")

test_that("function hrm_test", {
  expect_equal(result, true_result, tol = 1e-4)
  expect_output(print(result_hrm))
  expect_output(summary(result_hrm))
  expect_error(HRM::hrm_test(value~Var1*Var2*Var3, data = df, subject = "subject"))
})


true_result <- c(1.0000000, 9.0000000, 5.11735503, 0.08495685)
df$value2 <- exp(df$value)
result <- as.numeric(HRM::hrm_test(value~Var1*Var2*Var3*Var4, data = df, subject = "subject", nonparametric = TRUE, np.correction = FALSE)$result[1, 2:5])
result2 <- as.numeric(HRM::hrm_test(value2~Var1*Var2*Var3*Var4, data = df, subject = "subject", nonparametric = TRUE, np.correction = FALSE)$result[1, 2:5])
result3 <- as.numeric(HRM::hrm_test(value2~Var2*Var1*Var3*Var4, data = df, subject = "subject", nonparametric = TRUE, np.correction = FALSE)$result[2, 2:5])

result_hrm <- HRM::hrm_test(value~Var1*Var2*Var3*Var4, data = df, subject = "subject", nonparametric = TRUE, np.correction = FALSE)

test_that("function hrm_test nonparametric", {
  expect_equal(result, true_result, tol = 1e-4)
  expect_equal(result, result2, tol = 1e-4)
  expect_equal(result, result3, tol = 1e-4)
  expect_output(print(result_hrm))
  expect_output(summary(result_hrm))
  expect_error(HRM::hrm_test(value~Var1*Var2*Var3, data = df, subject = "subject", nonparametric = TRUE, np.correction = FALSE))
})