class TestMirtEquality(unittest.TestCase):
# Sets up a test.
@classmethod
def setUpClass(self):
# Read the data from the test data directory.
content = ''
with open(EXAM_DATA) as file_handle:
content = file_handle.read()
students = file_processing.to_student_array(content, prescored = True)
# Create the ltm test.
self.ltm_test = LtmTest(students, None)
# Create the mIRT test.
self.mirt_test = Test(students, None)
# Run ltm on the response matrix.
self.ltm_test.calculate_question_stats(store = False)
self.ltm_test.calculate_student_stats(store = False)
# Run mirt on the response matrix.
self.mirt_test.calculate_question_stats(store = False)
self.mirt_test.calculate_student_stats(store = False)
# Tests that the difference between discriminations calculated with mIRT and ltm is not too large.
def test_discriminations_equal(self):
for i in range(len(self.ltm_test.questions)):
ltm_discrimination = self.ltm_test.questions[i].get_discrimination()
mirt_discrimination = self.mirt_test.questions[i].get_discrimination()
self.assertAlmostEqual(ltm_discrimination, mirt_discrimination, delta = 0.03)
# Tests that the difference between item weights calculated with mIRT and ltm is not too large.
def test_item_weights_equal(self):
for i in range(len(self.ltm_test.questions)):
ltm_weight = self.ltm_test.questions[i].get_item_weight()
mirt_weight = self.mirt_test.questions[i].get_item_weight()
self.assertAlmostEqual(ltm_weight, mirt_weight, delta = 0.03)
# Tests that the difference between locations calculated with mIRT and ltm is not too large.
def test_item_weights_equal(self):
for i in range(len(self.ltm_test.students)):
ltm_location = self.ltm_test.students[i].get_location()
mirt_location = self.mirt_test.students[i].get_location()
self.assertAlmostEqual(ltm_location, mirt_location, delta = 0.03)
