def test_continuousMetaAnalysis(self):
# assert result is not None
studies = self.model.get_studies_in_current_order()
data_location = {'experimental_mean': 2, 'effect_size': 18, 'experimental_std_dev': 5, 'experimental_sample_size': 1, 'control_std_dev': 5, 'control_sample_size': 1, 'variance': 19, 'control_mean': 4}
data_type = CONTINUOUS
python_to_R.dataset_to_simple_continuous_robj(model=self.model,
included_studies=studies,
data_location=data_location,
data_type=data_type,
covs_to_include=[])
method = "continuous.random"
params = {'conf.level': 95.0, 'digits': 3, 'fp_col2_str': u'[default]', 'fp_show_col4': False, 'fp_xlabel': u'[default]', 'fp_col4_str': u'Ev/Ctrl', 'fp_xticks': '[default]', 'fp_col3_str': u'Ev/Trt', 'fp_show_col3': False, 'fp_show_col2': True, 'fp_show_col1': True, 'fp_plot_lb': '[default]', 'fp_outpath': u'./r_tmp/forest.png', 'rm.method': 'DL', 'fp_plot_ub': '[default]', 'fp_col1_str': u'Studies', 'measure': 'SMD', 'fp_show_summary_line': True}
result = python_to_R.run_continuous_ma(function_name=method,
params=params)
self.assertIsNotNone(result, "Result is unexpectedly none!")
