Data analysis for single-case designs is an issue that has prompted many researchers to propose a variety of alternatives, including use of randomisation tests, regression-based procedures, and standardised mean difference. Another option consists in computing unstandardised or raw differences between conditions: the changes in slope and in level, or the difference between the projected baseline (including trend) and the actual treatment phase measurements. Apart from the strengths of these procedures (potentially easier interpretation clinically, separate estimations and an overall quantification of effects, reasonable performance), they require further development, such as (a) creating extensions for dealing with methodologically strong designs such as multiple baseline, (b) achieving comparability across studies and making possible meta-analytical integrations, and (c) implementing software for the extensions. The proposals are illustrated herein in the context of a meta-analysis of 28 studies on (neuro)behavioural interventions in adults who have challenging behaviours after acquired brain injury.