All tests pass

Author: jmafoster1

causal_testing/testing/estimators.py

@@ -431,8 +431,6 @@ def estimate_control_treatment(self, adjustment_config: dict = None) -> tuple[pd
         model = self._run_linear_regression()
         self.model = model
 
-
-
         x = pd.DataFrame(columns=self.df.columns)
         x[self.treatment] = [self.treatment_value, self.control_value]
         x["Intercept"] = 1#self.intercept
@@ -532,7 +530,6 @@ def _run_linear_regression(self) -> RegressionResultsWrapper:
                 )
         # model = sm.OLS(outcome_col, treatment_and_adjustments_cols).fit()
         model = smf.ols(formula=self.formula, data=self.df).fit()
-        print(model.summary())
         return model
 
     def _get_confidence_intervals(self, model):

tests/json_front_tests/test_json_class.py

@@ -67,8 +67,6 @@ def test_argparse(self):
 
     def test_setup_modelling_scenario(self):
         self.json_class.setup()
-        print(type(self.json_class.modelling_scenario))
-        print(self.json_class.modelling_scenario)
         self.assertIsInstance(self.json_class.modelling_scenario, Scenario)
 
     def test_setup_causal_specification(self):

tests/testing_tests/test_causal_test_engine.py

@@ -218,8 +218,9 @@ def test_execute_test_observational_linear_regression_estimator_squared_term(sel
             self.minimal_adjustment_set,
             "C",
             self.causal_test_engine.scenario_execution_data_df,
+            formula=f"C ~ A + {'+'.join(self.minimal_adjustment_set)} + (D ** 2)"
         )
-        estimation_model.add_squared_term_to_df("D")
+        # estimation_model.add_squared_term_to_df("D")
         causal_test_result = self.causal_test_engine.execute_test(estimation_model, self.causal_test_case)
         self.assertAlmostEqual(round(causal_test_result.test_value.value, 1), 4, delta=1)
 

tests/testing_tests/test_estimators.py

@@ -200,11 +200,12 @@ def test_program_15_1A(self):
             "smokeyrs",
         }
         linear_regression_estimator = LinearRegressionEstimator("qsmk", 1, 0, covariates, "wt82_71", df,
-        formula="""wt82_71 ~ qsmk +
-                             age + np.power(age, 2) +
-                             wt71 + np.power(wt71, 2) +
-                             smokeintensity + np.power(smokeintensity, 2) +
-                             smokeyrs + np.power(smokeyrs, 2) +
+        formula=f"""wt82_71 ~ qsmk +
+                             {'+'.join(sorted(list(covariates)))} +
+                             np.power(age, 2) +
+                             np.power(wt71, 2) +
+                             np.power(smokeintensity, 2) +
+                             np.power(smokeyrs, 2) +
                              (qsmk * smokeintensity)""")
         # terms_to_square = ["age", "wt71", "smokeintensity", "smokeyrs"]
         # terms_to_product = [("qsmk", "smokeintensity")]
@@ -215,7 +216,7 @@ def test_program_15_1A(self):
 
         model = linear_regression_estimator._run_linear_regression()
         self.assertEqual(round(model.params["qsmk"], 1), 2.6)
-        self.assertEqual(round(model.params["qsmk*smokeintensity"], 2), 0.05)
+        self.assertEqual(round(model.params["qsmk:smokeintensity"], 2), 0.05)
 
     def test_program_15_no_interaction(self):
         """Test whether our linear regression implementation produces the same results as program 15.1 (p. 163, 184)