class_docstr: a wrapper class for two way anova type of analysis with OLS
  
  
  currently mainly to bring things together
  
  Notes
  -----
  unclear: adding multiple test might assume block design or orthogonality
  
  This estimates the full dummy version with OLS.
  The drop first dummy representation can be recovered through the
  transform method.
  
  TODO: add more methods, tests, pairwise, multiple, marginal effects
  try out what can be added for userfriendly access.
  
  missing: ANOVA table
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code: def ttest_conditional_effect(self, factorind):
      if factorind == 1:
          return self.resols.t_test(self.C1), self.C1_label
      else:
          return self.resols.t_test(self.C2), self.C2_label
  
imports: from numpy.testing import assert_equal
  import numpy
label_desc: Use image node_id 5 for calling the TwoWay obj's underlying member method code with example usage: obj.ttest_conditional_effect(factorind) and returns: self,  self, self,  self