code: def test_repeated_measures_aggregate_compare_with_ezANOVA():
      # Results should reproduces those from R's `ezANOVA` (library ez).
      ez = pd.DataFrame(
          {
              "F Value": [
                  8.7650709,
                  8.4985785,
                  20.5076546,
                  0.8457797,
                  21.7593382,
                  6.2416695,
                  5.4253359,
              ],
              "Num DF": [1, 2, 1, 2, 1, 2, 2],
              "Den DF": [7, 14, 7, 14, 7, 14, 14],
              "Pr > F": [
                  0.021087505,
                  0.003833921,
                  0.002704428,
                  0.450021759,
                  0.002301792,
                  0.011536846,
                  0.018010647,
              ],
          },
          index=pd.Index(["A", "B", "D", "A:B", "A:D", "B:D", "A:B:D"]),
      )
      ez = ez[["F Value", "Num DF", "Den DF", "Pr > F"]]
  
      double_data = pd.concat([data, data], axis=0)
      df = (
          AnovaRM(
              double_data,
              "DV",
              "id",
              within=["A", "B", "D"],
              aggregate_func=pd.Series.mean,
          )
          .fit()
          .anova_table
      )
  
      assert_frame_equal(ez, df, check_dtype=False)
  
file_path: statsmodels/statsmodels/stats/tests/test_anova_rm.py
imports: from statsmodels.compat.pandas import assert_frame_equal
  from numpy.testing import assert_array_almost_equal, assert_equal, assert_raises
  import pandas
  from statsmodels.stats.anova import AnovaRM
label_desc: Use image node_id 11 for calling a global function with example usage: test_repeated_measures_aggregate_compare_with_ezANOVA() without return types