code: def test_logrank_test_output_against_R_1():
      df = load_g3()
      ix = df["group"] == "RIT"
      d1, e1 = df.loc[ix]["time"], df.loc[ix]["event"]
      d2, e2 = df.loc[~ix]["time"], df.loc[~ix]["event"]
  
      expected = 0.0138
      result = stats.logrank_test(
          d1, d2, event_observed_A=e1, event_observed_B=e2
      )
      assert abs(result.p_value - expected) < 0.0001
  
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 4 for calling a global function with example usage: test_logrank_test_output_against_R_1() without return types