def _add_evidence(
            self,
            assoc_id,
            eco_id,
            p_value,
            percentage_change,
            effect_size,
            study_bnode
    ):
        """
        :param assoc_id: assoc curie used to reify a
        genotype to phenotype association, generated in _process_data()
        :param eco_id: eco_id as curie, hardcoded in _process_data()
        :param p_value: str, from self.files['all']
        :param percentage_change: str, from self.files['all']
        :param effect_size: str, from self.files['all']
        :param study_bnode: str, from self.files['all']
        :param phenotyping_center: str, from self.files['all']
        :return: str, evidence_line_bnode as curie
        """

        evidence_model = Evidence(self.graph, assoc_id)
        provenance_model = Provenance(self.graph)
        model = Model(self.graph)

        # Add line of evidence
        evidence_line_bnode = self.make_id(
            "{0}{1}".format(assoc_id, study_bnode), '_')
        evidence_model.add_supporting_evidence(evidence_line_bnode)
        model.addIndividualToGraph(evidence_line_bnode, None, eco_id)

        # Add supporting measurements to line of evidence
        measurements = {}
        if p_value is not None or p_value != "":
            p_value_bnode = self.make_id(
                "{0}{1}{2}".format(evidence_line_bnode, 'p_value', p_value), '_')
            model.addIndividualToGraph(p_value_bnode, None, self.globaltt['p-value'])
            try:
                measurements[p_value_bnode] = float(p_value)
            except ValueError:
                measurements[p_value_bnode] = p_value
        if percentage_change is not None and percentage_change != '':

            fold_change_bnode = self.make_id(
                "{0}{1}{2}".format(
                    evidence_line_bnode, 'percentage_change', percentage_change), '_')
            model.addIndividualToGraph(
                fold_change_bnode, None, self.resolve('percentage_change'))
            measurements[fold_change_bnode] = percentage_change
        if effect_size is not None or effect_size != "":
            fold_change_bnode = self.make_id(
                "{0}{1}{2}".format(
                    evidence_line_bnode, 'effect_size', effect_size), '_')
            model.addIndividualToGraph(
                fold_change_bnode, None, self.globaltt['effect size estimate'])
            measurements[fold_change_bnode] = effect_size

        evidence_model.add_supporting_data(evidence_line_bnode, measurements)

        # Link evidence to provenance by connecting to study node
        provenance_model.add_study_to_measurements(study_bnode, measurements.keys())
        self.graph.addTriple(
            evidence_line_bnode, self.globaltt['has_evidence_item_output_from'], study_bnode)

        return evidence_line_bnode
:param assoc_id: assoc curie used to reify a
        genotype to phenotype association, generated in _process_data()
        :param eco_id: eco_id as curie, hardcoded in _process_data()
        :param p_value: str, from self.files['all']
        :param percentage_change: str, from self.files['all']
        :param effect_size: str, from self.files['all']
        :param study_bnode: str, from self.files['all']
        :param phenotyping_center: str, from self.files['all']
        :return: str, evidence_line_bnode as curie