code: def test_multivariate_log_rank_is_identital_to_log_rank_for_n_equals_2():
      N = 200
      T1 = np.random.exponential(5, size=N)
      T2 = np.random.exponential(5, size=N)
      C1 = np.random.binomial(1, 0.9, size=N)
      C2 = np.random.binomial(1, 0.9, size=N)
      result = stats.logrank_test(T1, T2, C1, C2)
  
      T = np.r_[T1, T2]
      C = np.r_[C1, C2]
      G = np.array([1] * 200 + [2] * 200)
      result_m = stats.multivariate_logrank_test(T, G, C)
      assert result.p_value == result_m.p_value
  
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 25 for calling a global function with example usage: test_multivariate_log_rank_is_identital_to_log_rank_for_n_equals_2() without return types