code: def test_logrank_test_with_t_0():
      control_T = [
          1,
          1,
          2,
          2,
          3,
          4,
          4,
          5,
          5,
          8,
          8,
          8,
          8,
          11,
          11,
          12,
          12,
          15,
          17,
          22,
          23,
      ]
      control_E = np.ones_like(control_T)
  
      treatment_T = [
          6,
          6,
          6,
          7,
          10,
          13,
          16,
          22,
          23,
          6,
          9,
          10,
          11,
          17,
          19,
          20,
          25,
          32,
          32,
          34,
          25,
      ]
      treatment_E = [
          1,
          1,
          1,
          1,
          1,
          1,
          1,
          1,
          1,
          0,
          0,
          0,
          0,
          0,
          0,
          0,
          0,
          0,
          0,
          0,
          0,
      ]
  
      result = stats.logrank_test(
          control_T,
          treatment_T,
          event_observed_A=control_E,
          event_observed_B=treatment_E,
          t_0=10,
      )
  
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 6 for calling a global function with example usage: test_logrank_test_with_t_0() without return types