remove unnecessary kwargs in did experiments

Author: drbenvincent

causalpy/tests/test_input_validation.py

@@ -58,8 +58,6 @@ def test_did_validation_post_treatment_formula():
             formula="y ~ 1 + group*post_SOMETHING",
             time_variable_name="t",
             group_variable_name="group",
-            treated=1,
-            untreated=0,
             model=cp.pymc_models.LinearRegression(sample_kwargs=sample_kwargs),
         )
 
@@ -91,8 +89,6 @@ def test_did_validation_post_treatment_data():
             formula="y ~ 1 + group*post_treatment",
             time_variable_name="t",
             group_variable_name="group",
-            treated=1,
-            untreated=0,
             model=cp.pymc_models.LinearRegression(sample_kwargs=sample_kwargs),
         )
 
@@ -124,8 +120,6 @@ def test_did_validation_unit_data():
             formula="y ~ 1 + group*post_treatment",
             time_variable_name="t",
             group_variable_name="group",
-            treated=1,
-            untreated=0,
             model=cp.pymc_models.LinearRegression(sample_kwargs=sample_kwargs),
         )
 
@@ -157,8 +151,6 @@ def test_did_validation_group_dummy_coded():
             formula="y ~ 1 + group*post_treatment",
             time_variable_name="t",
             group_variable_name="group",
-            treated=1,
-            untreated=0,
             model=cp.pymc_models.LinearRegression(sample_kwargs=sample_kwargs),
         )
 

causalpy/tests/test_pymc_models.py

@@ -130,8 +130,6 @@ def test_idata_property():
         formula="y ~ 1 + group + t + group:post_treatment",
         time_variable_name="t",
         group_variable_name="group",
-        treated=1,
-        untreated=0,
         model=cp.pymc_models.LinearRegression(sample_kwargs=sample_kwargs),
     )
     assert hasattr(result, "idata")
@@ -157,17 +155,13 @@ def test_result_reproducibility(seed):
         formula="y ~ 1 + group + t + group:post_treatment",
         time_variable_name="t",
         group_variable_name="group",
-        treated=1,
-        untreated=0,
         model=cp.pymc_models.LinearRegression(sample_kwargs=sample_kwargs),
     )
     result2 = cp.DifferenceInDifferences(
         df,
         formula="y ~ 1 + group + t + group:post_treatment",
         time_variable_name="t",
         group_variable_name="group",
-        treated=1,
-        untreated=0,
         model=cp.pymc_models.LinearRegression(sample_kwargs=sample_kwargs),
     )
     assert np.all(result1.idata.posterior.mu == result2.idata.posterior.mu)