def test_example_4(self):
example = 'Heterogeneity: Chi? = 15.08, df= 10 (P = 0.13);\n‘Test for overall effect: Z = 9.01 (P < 0.00001)\n\n\n\n'
hetrogeneity, overall_effect = SPSSForestPlot._decode_footer_summary_ocr(
example)
self.assertEqual(dict(hetrogeneity), {
"Chi": 15.08,
"df": 10.0,
"P": 0.13
})
self.assertEqual(overall_effect, {"Z": 9.01, "P": 0.00001})
def test_example_6(self):
example = 'Heterogeneity: Chi? = 2.11, df = 5 (P = 0.83); 7 = 0%\nTest for overall effect: Z = 3.80 (P = 0.0001)\n\n'
hetrogeneity, overall_effect = SPSSForestPlot._decode_footer_summary_ocr(
example)
self.assertEqual(dict(hetrogeneity), {
"Chi": 2.11,
"df": 5.0,
"P": 0.83,
"I": 0.0
})
self.assertEqual(overall_effect, {"Z": 3.8, "P": 0.0001})
def test_example_2(self):
example = 'Heterogeneity: Chi? = 2.07, df= 10 (P= 1.00); /7= 0%\nTest for overall effect: Z= 1.13 (P = 0.26)\n\x0c'
hetrogeneity, overall_effect = SPSSForestPlot._decode_footer_summary_ocr(
example)
self.assertEqual(dict(hetrogeneity), {
"Chi": 2.07,
"df": 10.0,
"P": 1.00,
"I": 0.0
})
self.assertEqual(overall_effect, {"Z": 1.13, "P": 0.26})
def test_example_1(self):
example = 'Heterogeneity: Tau? = 0.00; Chi? = 2.98, df= 4 (P = 0.56), I= 0% |\nTest for overall effect: Z= 3.12'
hetrogeneity, overall_effect = SPSSForestPlot._decode_footer_summary_ocr(
example)
self.assertEqual(dict(hetrogeneity), {
"Tau": 0.00,
"Chi": 2.98,
"df": 4,
"P": 0.56,
"I": 0.0
})
self.assertEqual(overall_effect, {"Z": 3.12})