code: def test_fleiss_kappa_irr():
      fleiss = Holder()
      # > r = kappam.fleiss(diagnoses)
      # > cat_items(r, pref="fleiss.")
      fleiss.method = "Fleiss' Kappa for m Raters"
      fleiss.irr_name = "Kappa"
      fleiss.value = 0.4302445
      fleiss.stat_name = "z"
      fleiss.statistic = 17.65183
      fleiss.p_value = 0
      data_, _ = aggregate_raters(diagnoses)
      res1_kappa = fleiss_kappa(data_)
      assert_almost_equal(res1_kappa, fleiss.value, decimal=7)
  
imports: import numpy
  from numpy.testing import assert_almost_equal, assert_equal, assert_allclose
  from statsmodels.stats.inter_rater import fleiss_kappa, cohens_kappa, to_table, aggregate_raters
  from statsmodels.tools.testing import Holder
label_desc: Use image node_id 5 for calling a global function with example usage: test_fleiss_kappa_irr() without return types