context("check if gross inconsistencies/decision errors are correctly classified")

# test if the following cases are correctly identified as decision errors -----

# check classification of regular decision errors in all types of tests
test_that("simple decision errors are classified as such", {
  txt1  <- "t(28) = 2.20, p = .06"
  txt2  <- "t(28) = 1.20, p = .03"
  
  txt3  <- "F(2, 28) = 22.20, p = .06"
  txt4  <- "F(2, 28) = 2.20, p = .03"
  
  txt5  <- "r(28) = .22, p = .03"
  txt6  <- "r(28) = .52, p = .06"
  
  txt7  <- "chi2(28) = 2.20, p = .03"
  txt8  <- "chi2(28) = 52.20, p = .06"
  
  txt9  <- " z = 1.20, p = .03"
  txt10 <- " z = 2.20, p = .06"
  
  txt11 <- "Q(28) = 2.20, p = .03"
  txt12 <- "Q(28) = 52.20, p = .06"
  
  expect_true(statcheck(txt1,  messages = FALSE)[[VAR_DEC_ERROR]])
  expect_true(statcheck(txt2,  messages = FALSE)[[VAR_DEC_ERROR]])
  expect_true(statcheck(txt3,  messages = FALSE)[[VAR_DEC_ERROR]])
  expect_true(statcheck(txt4,  messages = FALSE)[[VAR_DEC_ERROR]])
  expect_true(statcheck(txt5,  messages = FALSE)[[VAR_DEC_ERROR]])
  expect_true(statcheck(txt6,  messages = FALSE)[[VAR_DEC_ERROR]])
  expect_true(statcheck(txt7,  messages = FALSE)[[VAR_DEC_ERROR]])
  expect_true(statcheck(txt8,  messages = FALSE)[[VAR_DEC_ERROR]])
  expect_true(statcheck(txt9,  messages = FALSE)[[VAR_DEC_ERROR]])
  expect_true(statcheck(txt10, messages = FALSE)[[VAR_DEC_ERROR]])
  expect_true(statcheck(txt11, messages = FALSE)[[VAR_DEC_ERROR]])
  expect_true(statcheck(txt12, messages = FALSE)[[VAR_DEC_ERROR]])
})

# test if different arguments concerning decision errors work -----------------

# alpha: detect decision errors for different alpha levels
test_that("decision errors are correctly classified when alpha levels are changed", {
  # all cases below are errors
  txt1 <- "t(28) = 2.20, p = .06"
  txt2 <- "t(28) = 1.20, p = .03"
  
  txt3 <- "t(28) = 2.20, p = .11"
  txt4 <- "t(28) = 1.20, p = .09"
  
  txt5 <- "t(28) = 5.20, p = .02"
  txt6 <- "t(28) = 1.20, p = .005"
  
  expect_true(statcheck(txt1, messages = FALSE, alpha = .05)[[VAR_DEC_ERROR]])
  expect_true(statcheck(txt2, messages = FALSE, alpha = .05)[[VAR_DEC_ERROR]])
  
  expect_true(statcheck(txt3, messages = FALSE, alpha = .10)[[VAR_DEC_ERROR]])
  expect_true(statcheck(txt4, messages = FALSE, alpha = .10)[[VAR_DEC_ERROR]])
  
  expect_true(statcheck(txt5, messages = FALSE, alpha = .01)[[VAR_DEC_ERROR]])
  expect_true(statcheck(txt6, messages = FALSE, alpha = .01)[[VAR_DEC_ERROR]])
})

# pEqualAlphaSig: should p = .05 be considered significant or not
test_that("decision errors are correctly classified when argument p = alpha is changed", {
  
  txt1 <- "t(28) = 2.20, p = .05"
  txt2 <- "t(28) = 2.20, p = .10"
  
  expect_false(statcheck(txt1, messages = FALSE)[[VAR_DEC_ERROR]])
  expect_true(statcheck(txt1, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  
  # check pEqualAlphaSig for different alpha
  expect_false(statcheck(txt2, messages = FALSE, alpha = .10)[[VAR_DEC_ERROR]])
  expect_true(statcheck(txt2, messages = FALSE, pEqualAlphaSig = FALSE, 
                        alpha = .10)[[VAR_DEC_ERROR]])

})


# test classifications of (in)exact test statistcs and (in)exact p-values ----

# test statistics exactly reported & p-value exactly reported
test_that("cases where t = ..., p = ... are correctly classified", {
  
  # assume alpha = .05
  # calculate which t-values correspond to p-values of .04, .05, and .06
  t.04 <- qt(.04/2, 28, lower.tail = FALSE)
  t.05 <- qt(.05/2, 28, lower.tail = FALSE)
  t.06 <- qt(.06/2, 28, lower.tail = FALSE)
  
  txt1 <- paste0("t(28) = ", t.04, ", p = .04")
  txt2a <- paste0("t(28) = ", t.05 + .0001, ", p = .04") # approach computed p == .05
  txt2b <- paste0("t(28) = ", t.05 - .0001, ", p = .04") # approach computed p == .05
  txt3 <- paste0("t(28) = ", t.06, ", p = .04")
  
  txt4 <- paste0("t(28) = ", t.04, ", p = .05")
  txt5 <- paste0("t(28) = ", t.05, ", p = .05")
  txt6 <- paste0("t(28) = ", t.06, ", p = .05")
  
  txt7 <- paste0("t(28) = ", t.04, ", p = .06")
  txt8a <- paste0("t(28) = ", t.05 + .0001, ", p = .06") # approach computed p == .05
  txt8b <- paste0("t(28) = ", t.05 - .0001, ", p = .06") # approach computed p == .05
  txt9 <- paste0("t(28) = ", t.06, ", p = .06")
  
  # if pEqualSig == TRUE
  expect_false(statcheck(txt1, messages = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt2a, messages = FALSE)[[VAR_DEC_ERROR]])
  expect_true(statcheck(txt3, messages = FALSE)[[VAR_DEC_ERROR]])
  
  expect_false(statcheck(txt4, messages = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt5, messages = FALSE)[[VAR_DEC_ERROR]])
  expect_true(statcheck(txt6, messages = FALSE)[[VAR_DEC_ERROR]])
  
  expect_true(statcheck(txt7, messages = FALSE)[[VAR_DEC_ERROR]])
  expect_true(statcheck(txt8a, messages = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt9, messages = FALSE)[[VAR_DEC_ERROR]])
  
  # if pEqualSig == FALSE
  expect_false(statcheck(txt1, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  expect_true(statcheck(txt2b, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  expect_true(statcheck(txt3, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  
  expect_true(statcheck(txt4, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt5, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt6, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  
  expect_true(statcheck(txt7, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt8b, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt9, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
})

# test statistics exactly reported & p-value < ...
test_that("cases where t = ..., p < ... are correctly classified", {
  
  # assume alpha = .05
  # calculate which t-values correspond to p-values of .04, .05, and .06
  t.04 <- qt(.04/2, 28, lower.tail = FALSE)
  t.05 <- qt(.05/2, 28, lower.tail = FALSE)
  t.06 <- qt(.06/2, 28, lower.tail = FALSE)
  
  txt1 <- paste0("t(28) = ", t.04 - .001, ", p < .04")   # approach computed p == .04
  txt2a <- paste0("t(28) = ", t.05 + .0001, ", p < .04") # approach computed p == .05
  txt2b <- paste0("t(28) = ", t.05 - .0001, ", p < .04") # approach computed p == .05
  txt3 <- paste0("t(28) = ", t.06, ", p < .04")
  
  txt4 <- paste0("t(28) = ", t.04, ", p < .05")
  txt5a <- paste0("t(28) = ", t.05 + .0001, ", p < .0500") # approach computed p == .05
  txt5b <- paste0("t(28) = ", t.05 - .0001, ", p < .0500") # approach computed p == .05
  txt6 <- paste0("t(28) = ", t.06, ", p < .05")
  
  txt7 <- paste0("t(28) = ", t.04, ", p < .06")
  txt8a <- paste0("t(28) = ", t.05 + .0001, ", p < .06") # approach computed p == .05
  txt8b <- paste0("t(28) = ", t.05 - .0001, ", p < .06") # approach computed p == .05
  txt9 <- paste0("t(28) = ", t.06, ", p < .06")
  
  # if pEqualSig == TRUE
  expect_false(statcheck(txt1, messages = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt2a, messages = FALSE)[[VAR_DEC_ERROR]])
  expect_true(statcheck(txt3, messages = FALSE)[[VAR_DEC_ERROR]])
  
  expect_false(statcheck(txt4, messages = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt5a, messages = FALSE)[[VAR_DEC_ERROR]])
  expect_true(statcheck(txt6, messages = FALSE)[[VAR_DEC_ERROR]])
  
  expect_false(statcheck(txt7, messages = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt8a, messages = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt9, messages = FALSE)[[VAR_DEC_ERROR]])
  
  # if pEqualSig == FALSE
  expect_false(statcheck(txt1, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  expect_true(statcheck(txt2b, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  expect_true(statcheck(txt3, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  
  expect_false(statcheck(txt4, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  expect_true(statcheck(txt5b, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  expect_true(statcheck(txt6, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  
  expect_false(statcheck(txt7, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt8b, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt9, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
})

# test statistics exactly reported & p-value > ...
test_that("cases where t = ..., p > ... are correctly classified", {
  
  # assume alpha = .05
  # calculate which t-values correspond to p-values of .04, .05, and .06
  t.04 <- qt(.04/2, 28, lower.tail = FALSE)
  t.05 <- qt(.05/2, 28, lower.tail = FALSE)
  t.06 <- qt(.06/2, 28, lower.tail = FALSE)
  
  txt1 <- paste0("t(28) = ", t.04 + .001, ", p > .04") # approach computed p == .04
  txt2a <- paste0("t(28) = ", t.05 + .0001, ", p > .04") # approach computed p == .05
  txt2b <- paste0("t(28) = ", t.05 - .0001, ", p > .04") # approach computed p == .05
  txt3 <- paste0("t(28) = ", t.06, ", p > .04")
  
  txt4 <- paste0("t(28) = ", t.04, ", p > .05")
  txt5a <- paste0("t(28) = ", t.05 + .0001, ", p > .05") # approach computed p == .05
  txt5b <- paste0("t(28) = ", t.05 - .0001, ", p > .05") # approach computed p == .05
  txt6 <- paste0("t(28) = ", t.06, ", p > .05")
  
  txt7 <- paste0("t(28) = ", t.04, ", p > .06")
  txt8a <- paste0("t(28) = ", t.05 + .0001, ", p > .06") # approach computed p == .05
  txt8b <- paste0("t(28) = ", t.05 - .0001, ", p > .06") # approach computed p == .05
  txt9 <- paste0("t(28) = ", t.06, ", p > .06")
  
  # if pEqualSig == TRUE
  expect_false(statcheck(txt1, messages = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt2a, messages = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt3, messages = FALSE)[[VAR_DEC_ERROR]])
  
  expect_true(statcheck(txt4, messages = FALSE)[[VAR_DEC_ERROR]])
  expect_true(statcheck(txt5a, messages = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt6, messages = FALSE)[[VAR_DEC_ERROR]])
  
  expect_true(statcheck(txt7, messages = FALSE)[[VAR_DEC_ERROR]])
  expect_true(statcheck(txt8a, messages = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt9, messages = FALSE)[[VAR_DEC_ERROR]])
  
  # if pEqualSig == FALSE
  expect_false(statcheck(txt1, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt2b, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt3, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  
  expect_true(statcheck(txt4, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt5b, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt6, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  
  expect_true(statcheck(txt7, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt8b, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt9, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
})

# test statistics < & p-value exactly reported
test_that("cases where t < ..., p = ... are correctly classified", {
  
  # assume alpha = .05
  # calculate which t-values correspond to p-values of .04, .05, and .06
  t.04 <- qt(.04/2, 28, lower.tail = FALSE)
  t.05 <- qt(.05/2, 28, lower.tail = FALSE)
  t.06 <- qt(.06/2, 28, lower.tail = FALSE)
  
  txt1 <- paste0("t(28) < ", t.04 - .001, ", p = .0400") # approach computed p == .04
  txt2 <- paste0("t(28) < ", t.05 - .0001, ", p = .04") # approach computed p == .05
  txt3 <- paste0("t(28) < ", t.06, ", p = .04")
  
  txt4 <- paste0("t(28) < ", t.04, ", p = .05")
  txt5 <- paste0("t(28) < ", t.05 - .001, ", p = .0500") # approach computed p == .05
  txt6 <- paste0("t(28) < ", t.06, ", p = .05")
  
  txt7 <- paste0("t(28) < ", t.04, ", p = .06")
  txt8 <- paste0("t(28) < ", t.05 - .0001, ", p = .0600") # approach computed p == .05
  txt9 <- paste0("t(28) < ", t.06 - .001, ", p = .0600") # approach computed p == .06
  
  # if pEqualSig == TRUE
  expect_false(statcheck(txt1, messages = FALSE)[[VAR_DEC_ERROR]])
  expect_true(statcheck(txt2, messages = FALSE)[[VAR_DEC_ERROR]])
  expect_true(statcheck(txt3, messages = FALSE)[[VAR_DEC_ERROR]])
  
  expect_false(statcheck(txt4, messages = FALSE)[[VAR_DEC_ERROR]])
  expect_true(statcheck(txt5, messages = FALSE)[[VAR_DEC_ERROR]])
  expect_true(statcheck(txt6, messages = FALSE)[[VAR_DEC_ERROR]])
  
  expect_false(statcheck(txt7, messages = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt8, messages = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt9, messages = FALSE)[[VAR_DEC_ERROR]])
  
  # if pEqualSig == FALSE
  expect_false(statcheck(txt1, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  expect_true(statcheck(txt2, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  expect_true(statcheck(txt3, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  
  expect_false(statcheck(txt4, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt5, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt6, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  
  expect_false(statcheck(txt7, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt8, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt9, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
})

# test statistics < & p-value <
test_that("cases where t < ..., p < ... are correctly classified", {
  
  # assume alpha = .05
  # calculate which t-values correspond to p-values of .04, .05, and .06
  t.04 <- qt(.04/2, 28, lower.tail = FALSE)
  t.05 <- qt(.05/2, 28, lower.tail = FALSE)
  t.06 <- qt(.06/2, 28, lower.tail = FALSE)
  
  txt1 <- paste0("t(28) < ", t.04, ", p < .04")
  txt2 <- paste0("t(28) < ", t.05 - .0001, ", p < .04") # approach computed p == .05
  txt3 <- paste0("t(28) < ", t.06, ", p < .04")
  
  txt4 <- paste0("t(28) < ", t.04, ", p < .05")
  txt5 <- paste0("t(28) < ", t.05 - .0001, ", p < .05") # approach computed p == .05
  txt6 <- paste0("t(28) < ", t.06, ", p < .05")
  
  txt7 <- paste0("t(28) < ", t.04, ", p < .06")
  txt8 <- paste0("t(28) < ", t.05 - .0001, ", p < .06") # approach computed p == .05
  txt9 <- paste0("t(28) < ", t.06, ", p < .06")
  
  # if pEqualSig == TRUE
  expect_false(statcheck(txt1, messages = FALSE)[[VAR_DEC_ERROR]])
  expect_true(statcheck(txt2, messages = FALSE)[[VAR_DEC_ERROR]])
  expect_true(statcheck(txt3, messages = FALSE)[[VAR_DEC_ERROR]])
  
  expect_false(statcheck(txt4, messages = FALSE)[[VAR_DEC_ERROR]])
  expect_true(statcheck(txt5, messages = FALSE)[[VAR_DEC_ERROR]])
  expect_true(statcheck(txt6, messages = FALSE)[[VAR_DEC_ERROR]])
  
  expect_false(statcheck(txt7, messages = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt8, messages = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt9, messages = FALSE)[[VAR_DEC_ERROR]])
  
  # if pEqualSig == FALSE
  expect_false(statcheck(txt1, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  expect_true(statcheck(txt2, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  expect_true(statcheck(txt3, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  
  expect_false(statcheck(txt4, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  expect_true(statcheck(txt5, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  expect_true(statcheck(txt6, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  
  expect_false(statcheck(txt7, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt8, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt9, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
})

# test statistics < & p-value >
test_that("cases where t < ..., p > ... are correctly classified", {
  
  # assume alpha = .05
  # calculate which t-values correspond to p-values of .04, .05, and .06
  t.04 <- qt(.04/2, 28, lower.tail = FALSE)
  t.05 <- qt(.05/2, 28, lower.tail = FALSE)
  t.06 <- qt(.06/2, 28, lower.tail = FALSE)
  
  txt1 <- paste0("t(28) < ", t.04, ", p > .04")
  txt2 <- paste0("t(28) < ", t.05 - .0001, ", p > .04") # approach computed p == .05
  txt3 <- paste0("t(28) < ", t.06, ", p > .04")
  
  txt4 <- paste0("t(28) < ", t.04, ", p > .05")
  txt5 <- paste0("t(28) < ", t.05 - .0001, ", p > .05") # approach computed p == .05
  txt6 <- paste0("t(28) < ", t.06, ", p > .05")
  
  txt7 <- paste0("t(28) < ", t.04, ", p > .06")
  txt8 <- paste0("t(28) < ", t.05 - .0001, ", p > .06") # approach computed p == .05
  txt9 <- paste0("t(28) < ", t.06, ", p > .06")
  
  # if pEqualSig == TRUE
  expect_false(statcheck(txt1, messages = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt2, messages = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt3, messages = FALSE)[[VAR_DEC_ERROR]])
  
  expect_false(statcheck(txt4, messages = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt5, messages = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt6, messages = FALSE)[[VAR_DEC_ERROR]])
  
  expect_false(statcheck(txt7, messages = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt8, messages = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt9, messages = FALSE)[[VAR_DEC_ERROR]])
  
  # if pEqualSig == FALSE
  expect_false(statcheck(txt1, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt2, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt3, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  
  expect_false(statcheck(txt4, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt5, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt6, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  
  expect_false(statcheck(txt7, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt8, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt9, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
})

# test statistics > & p-value exactly reported
test_that("cases where t > ..., p = ... are correctly classified", {
  
  # assume alpha = .05
  # calculate which t-values correspond to p-values of .04, .05, and .06
  t.04 <- qt(.04/2, 28, lower.tail = FALSE)
  t.05 <- qt(.05/2, 28, lower.tail = FALSE)
  t.06 <- qt(.06/2, 28, lower.tail = FALSE)
  
  txt1 <- paste0("t(28) > ", t.04 + .001, ", p = .0400") # approach computed p == .04
  txt2 <- paste0("t(28) > ", t.05 + .0001, ", p = .04") # approach computed p == .05
  txt3 <- paste0("t(28) > ", t.06, ", p = .04")
  
  txt4 <- paste0("t(28) > ", t.04, ", p = .05")
  txt5 <- paste0("t(28) > ", t.05 + .001, ", p = .0500") # approach computed p == .05
  txt6 <- paste0("t(28) > ", t.06, ", p = .05")
  
  txt7 <- paste0("t(28) > ", t.04, ", p = .06")
  txt8 <- paste0("t(28) > ", t.05 + .001, ", p = .0600") # approach computed p == .05
  txt9 <- paste0("t(28) > ", t.06 + .001, ", p = .0600") # approach computed p == .06
  
  # if pEqualSig == TRUE
  expect_false(statcheck(txt1, messages = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt2, messages = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt3, messages = FALSE)[[VAR_DEC_ERROR]])
  
  expect_false(statcheck(txt4, messages = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt5, messages = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt6, messages = FALSE)[[VAR_DEC_ERROR]])
  
  expect_true(statcheck(txt7, messages = FALSE)[[VAR_DEC_ERROR]])
  expect_true(statcheck(txt8, messages = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt9, messages = FALSE)[[VAR_DEC_ERROR]])
  
  # if pEqualSig == FALSE
  expect_false(statcheck(txt1, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt2, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt3, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  
  expect_true(statcheck(txt4, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  expect_true(statcheck(txt5, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt6, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  
  expect_true(statcheck(txt7, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  expect_true(statcheck(txt8, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt9, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
})

# test statistics > & p-value <
test_that("cases where t > ..., p < ... are correctly classified", {
  
  # assume alpha = .05
  # calculate which t-values correspond to p-values of .04, .05, and .06
  t.04 <- qt(.04/2, 28, lower.tail = FALSE)
  t.05 <- qt(.05/2, 28, lower.tail = FALSE)
  t.06 <- qt(.06/2, 28, lower.tail = FALSE)
  
  txt1 <- paste0("t(28) > ", t.04 + .001, ", p < .0400") # approach computed p == .04
  txt2 <- paste0("t(28) > ", t.05 + .0001, ", p < .04") # approach computed p == .05
  txt3 <- paste0("t(28) > ", t.06, ", p < .04")
  
  txt4 <- paste0("t(28) > ", t.04, ", p < .05")
  txt5 <- paste0("t(28) > ", t.05 + .001, ", p < .0500") # approach computed p == .05
  txt6 <- paste0("t(28) > ", t.06, ", p < .05")
  
  txt7 <- paste0("t(28) > ", t.04, ", p < .06")
  txt8 <- paste0("t(28) > ", t.05 + .001, ", p < .0600") # approach computed p == .05
  txt9 <- paste0("t(28) > ", t.06 + .001, ", p < .0600") # approach computed p == .06
  
  # if pEqualSig == TRUE
  expect_false(statcheck(txt1, messages = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt2, messages = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt3, messages = FALSE)[[VAR_DEC_ERROR]])
  
  expect_false(statcheck(txt4, messages = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt5, messages = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt6, messages = FALSE)[[VAR_DEC_ERROR]])
  
  expect_false(statcheck(txt7, messages = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt8, messages = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt9, messages = FALSE)[[VAR_DEC_ERROR]])
  
  # if pEqualSig == FALSE
  expect_false(statcheck(txt1, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt2, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt3, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  
  expect_false(statcheck(txt4, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt5, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt6, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  
  expect_false(statcheck(txt7, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt8, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt9, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
})

# test statistics > & p-value >
test_that("cases where t > ..., p > ... are correctly classified", {
  
  # assume alpha = .05
  # calculate which t-values correspond to p-values of .04, .05, and .06
  t.04 <- qt(.04/2, 28, lower.tail = FALSE)
  t.05 <- qt(.05/2, 28, lower.tail = FALSE)
  t.06 <- qt(.06/2, 28, lower.tail = FALSE)
  
  txt1 <- paste0("t(28) > ", t.04 + .001, ", p > .0400") # approach computed p == .04
  txt2 <- paste0("t(28) > ", t.05 + .0001, ", p > .04") # approach computed p == .05
  txt3 <- paste0("t(28) > ", t.06, ", p > .04")
  
  txt4 <- paste0("t(28) > ", t.04, ", p > .05")
  txt5 <- paste0("t(28) > ", t.05 + .001, ", p > .0500") # approach computed p == .05
  txt6 <- paste0("t(28) > ", t.06, ", p > .05")
  
  txt7 <- paste0("t(28) > ", t.04, ", p > .06")
  txt8 <- paste0("t(28) > ", t.05 + .001, ", p > .0600") # approach computed p == .05
  txt9 <- paste0("t(28) > ", t.06 + .001, ", p > .0600") # approach computed p == .06
  
  # if pEqualSig == TRUE
  expect_false(statcheck(txt1, messages = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt2, messages = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt3, messages = FALSE)[[VAR_DEC_ERROR]])
  
  expect_true(statcheck(txt4, messages = FALSE)[[VAR_DEC_ERROR]])
  expect_true(statcheck(txt5, messages = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt6, messages = FALSE)[[VAR_DEC_ERROR]])
  
  expect_true(statcheck(txt7, messages = FALSE)[[VAR_DEC_ERROR]])
  expect_true(statcheck(txt8, messages = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt9, messages = FALSE)[[VAR_DEC_ERROR]])
  
  # if pEqualSig == FALSE
  expect_false(statcheck(txt1, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt2, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt3, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  
  expect_true(statcheck(txt4, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  expect_true(statcheck(txt5, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt6, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  
  expect_true(statcheck(txt7, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  expect_true(statcheck(txt8, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
  expect_false(statcheck(txt9, messages = FALSE, pEqualAlphaSig = FALSE)[[VAR_DEC_ERROR]])
})