diff --git a/causal_testing/surrogate/causal_surrogate_assisted.py b/causal_testing/surrogate/causal_surrogate_assisted.py
index c30b2086..c67d4e4b 100644
--- a/causal_testing/surrogate/causal_surrogate_assisted.py
+++ b/causal_testing/surrogate/causal_surrogate_assisted.py
@@ -9,6 +9,7 @@
 from causal_testing.testing.base_test_case import BaseTestCase
 from causal_testing.testing.estimators import CubicSplineRegressionEstimator
 
+
 @dataclass
 class SimulationResult:
     """Data class holding the data and result metadata of a simulation"""
@@ -19,7 +20,7 @@ class SimulationResult:
 
     def to_dataframe(self) -> pd.DataFrame:
         """Convert the simulation result data to a pandas DataFrame"""
-        data_as_lists = {k: v if isinstance(v, list) else [v] for k,v in self.data.items()}
+        data_as_lists = {k: v if isinstance(v, list) else [v] for k, v in self.data.items()}
         return pd.DataFrame(data_as_lists)
 
 
diff --git a/causal_testing/testing/estimators.py b/causal_testing/testing/estimators.py
index 3920e1f2..ffe76387 100644
--- a/causal_testing/testing/estimators.py
+++ b/causal_testing/testing/estimators.py
@@ -823,7 +823,7 @@ def estimate_hazard_ratio(self):
 
         #  IPCW step 4: Use these weights in a weighted analysis of the outcome model
         # Estimate the KM graph and IPCW hazard ratio using Cox regression.
-        cox_ph = CoxPHFitter()
+        cox_ph = CoxPHFitter(alpha=self.alpha)
         cox_ph.fit(
             df=preprocessed_data,
             duration_col="tout",