class_docstr: class for two sample comparison
  
  The tests and the confidence interval work for multi-endpoint comparison:
  If d1 and d2 have the same number of rows, then each column of the data
  in d1 is compared with the corresponding column in d2.
  
  Parameters
  ----------
  d1, d2 : instances of DescrStatsW
  
  Notes
  -----
  The result for the statistical tests and the confidence interval are
  independent of the user specified ddof.
  
  TODO: Extend to any number of groups or write a version that works in that
  case, like in SAS and SPSS.
code: def std_meandiff_separatevar(self):
      # this uses ``_var`` to use ddof=0 for formula
      d1 = self.d1
      d2 = self.d2
      return np.sqrt(d1._var / (d1.nobs - 1) + d2._var / (d2.nobs - 1))
  
imports: import numpy
  from scipy import stats
  from statsmodels.tools.decorators import cache_readonly
label_desc: Use image node_id 4 for calling the CompareMeans obj's underlying member method code with example usage: obj.std_meandiff_separatevar() and returns: np