parameters: (group_1, group_2, axis=None)
return_statement: return 1 - norm.cdf(W)
docstring: Compares the medians from two independent groups along the given axis.
  
      The comparison is performed using the McKean-Schrader estimate of the
      standard error of the medians.
  
      Parameters
      ----------
      group_1 : array_like
          First dataset.  Has to be of size >=7.
      group_2 : array_like
          Second dataset.  Has to be of size >=7.
      axis : int, optional
          Axis along which the medians are estimated. If None, the arrays are
          flattened.  If `axis` is not None, then `group_1` and `group_2`
          should have the same shape.
  
      Returns
      -------
      compare_medians_ms : {float, ndarray}
          If `axis` is None, then returns a float, otherwise returns a 1-D
          ndarray of floats with a length equal to the length of `group_1`
          along `axis`.
docstring_summary: Compares the medians from two independent groups along the given axis.
docstring_tokens: Compares the medians from two independent groups along the given axis .
function: def compare_medians_ms(group_1, group_2, axis=None):
      """
      Compares the medians from two independent groups along the given axis.
  
      The comparison is performed using the McKean-Schrader estimate of the
      standard error of the medians.
  
      Parameters
      ----------
      group_1 : array_like
          First dataset.  Has to be of size >=7.
      group_2 : array_like
          Second dataset.  Has to be of size >=7.
      axis : int, optional
          Axis along which the medians are estimated. If None, the arrays are
          flattened.  If `axis` is not None, then `group_1` and `group_2`
          should have the same shape.
  
      Returns
      -------
      compare_medians_ms : {float, ndarray}
          If `axis` is None, then returns a float, otherwise returns a 1-D
          ndarray of floats with a length equal to the length of `group_1`
          along `axis`.
  
      """
      (med_1, med_2) = (ma.median(group_1,axis=axis), ma.median(group_2,axis=axis))
      (std_1, std_2) = (mstats.stde_median(group_1, axis=axis),
                        mstats.stde_median(group_2, axis=axis))
      W = np.abs(med_1 - med_2) / ma.sqrt(std_1**2 + std_2**2)
      return 1 - norm.cdf(W)
function_tokens: def compare_medians_ms ( group_1 , group_2 , axis = None ) : ( med_1 , med_2 ) = ( ma . median ( group_1 , axis = axis ) , ma . median ( group_2 , axis = axis ) ) ( std_1 , std_2 ) = ( mstats . stde_median ( group_1 , axis = axis ) , mstats . stde_median ( group_2 , axis = axis ) ) W = np . abs ( med_1 - med_2 ) / ma . sqrt ( std_1 ** 2 + std_2 ** 2 ) return 1 - norm . cdf ( W )