code: def test_multivariate_logrank_on_dd_dataset():
      """
      library('survival')
      dd = read.csv('~/code/lifelines/lifelines/datasets/dd.csv')
      results = survdiff(Surv(duration, observed)~regime, data=dd, rho=0)
      results[5]
      """
      dd = load_dd()
      results = stats.multivariate_logrank_test(
          dd["duration"], dd["regime"], dd["observed"]
      )
      assert abs(results.test_statistic - 322.5991) < 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 9 for calling a global function with example usage: test_multivariate_logrank_on_dd_dataset() without return types