def score_(self):
        """
        The concordance score (also known as the c-index) of the fit.  The c-index is a generalization of the ROC AUC
        to survival data, including censorships.

        For this purpose, the ``score_`` is a measure of the predictive accuracy of the fitted model
        onto the training dataset.

        References
        ----------
        https://stats.stackexchange.com/questions/133817/stratified-concordance-index-survivalsurvconcordance

        """
        # pylint: disable=access-member-before-definition
        if not hasattr(self, "_concordance_score_"):
            if self.strata:
                # https://stats.stackexchange.com/questions/133817/stratified-concordance-index-survivalsurvconcordance
                num_correct, num_tied, num_pairs = 0, 0, 0
                for _, _df in self._predicted_partial_hazards_.groupby(self.strata):
                    if _df.shape[0] == 1:
                        continue
                    _num_correct, _num_tied, _num_pairs = _concordance_summary_statistics(
                        _df["T"].values, -_df["P"].values, _df["E"].values
                    )
                    num_correct += _num_correct
                    num_tied += _num_tied
                    num_pairs += _num_pairs
            else:
                df = self._predicted_partial_hazards_
                num_correct, num_tied, num_pairs = _concordance_summary_statistics(
                    df["T"].values, -df["P"].values, df["E"].values
                )

            self._concordance_score_ = _concordance_ratio(num_correct, num_tied, num_pairs)
            return self._concordance_score_
        return self._concordance_score_