Stratifies the sample based on propensity score using the
		bin selection procedure suggested by [1]_.

		The bin selection algorithm is based on a sequence of
		two-sample t tests performed on the log-odds ratio.

		This method should only be executed after the propensity score
		has been estimated.

		References
		----------
		.. [1] Imbens, G. & Rubin, D. (2015). Causal Inference in
			Statistics, Social, and Biomedical Sciences: An
			Introduction.

def stratify_s(self):

		"""
		Stratifies the sample based on propensity score using the
		bin selection procedure suggested by [1]_.

		The bin selection algorithm is based on a sequence of
		two-sample t tests performed on the log-odds ratio.

		This method should only be executed after the propensity score
		has been estimated.

		References
		----------
		.. [1] Imbens, G. & Rubin, D. (2015). Causal Inference in
			Statistics, Social, and Biomedical Sciences: An
			Introduction.
		"""

		pscore_order = self.raw_data['pscore'].argsort()
		pscore = self.raw_data['pscore'][pscore_order]
		D = self.raw_data['D'][pscore_order]
		logodds = np.log(pscore / (1-pscore))
		K = self.raw_data['K']

		blocks_uniq = set(select_blocks(pscore, logodds, D, K, 0, 1))
		self.blocks = sorted(blocks_uniq)
		self.stratify()