code: def test_unequal_intensity_event_observed():
      data1 = np.random.exponential(5, size=(2000, 1))
      data2 = np.random.exponential(1, size=(2000, 1))
      eventA = np.random.binomial(1, 0.5, size=(2000, 1))
      eventB = np.random.binomial(1, 0.5, size=(2000, 1))
      result = stats.logrank_test(
          data1, data2, event_observed_A=eventA, event_observed_B=eventB
      )
      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 14 for calling a global function with example usage: test_unequal_intensity_event_observed() without return types