code: def trim_s(self):
  
  		
  
  		pscore = self.raw_data['pscore']
  		g = 1.0/(pscore*(1-pscore))  # 1 over Bernoulli variance
  
  		self.cutoff = select_cutoff(g)
  		self.trim()
docs: Trims data based on propensity score using the cutoff
  		selection algorithm suggested by [1]_.
  		
  		This method should only be executed after the propensity score
  		has been estimated.
  
  		References
  		----------
  		.. [1] Crump, R., Hotz, V., Imbens, G., & Mitnik, O. (2009).
  			Dealing with Limited Overlap in Estimation of
  			Average Treatment Effects. Biometrika, 96, 187-199.