code: def test_survival_difference_at_fixed_point_in_time_test_parametric():
      df = load_waltons()
      ix = df["group"] == "miR-137"
      wf1 = WeibullFitter().fit(df.loc[ix]["T"], df.loc[ix]["E"])
      wf2 = WeibullFitter().fit(df.loc[~ix]["T"], df.loc[~ix]["E"])
      result = stats.survival_difference_at_fixed_point_in_time_test(
          10, wf1, wf2
      )
      assert result.p_value < 0.05
  
imports: import numpy
  import pandas
  import numpy.testing
  import pytest
  from pandas.testing import assert_frame_equal
  from lifelines import statistics
  from lifelines import CoxPHFitter, KaplanMeierFitter, WeibullFitter
  from lifelines.exceptions import StatisticalWarning
  from lifelines.datasets import load_waltons, load_g3, load_lymphoma, load_dd, load_regression_dataset, load_leukemia
label_desc: Use image node_id 39 for calling a global function with example usage: test_survival_difference_at_fixed_point_in_time_test_parametric() without return types