To investigate the generalizability of the results of single-case experimental studies, evaluating the effect of one or more treatments, in applied research various simultaneous and sequential replication strategies are used. We discuss one approach for aggregating the results for single-cases: the use of hierarchical linear models. This approach has the potential to allow making improved inferences about the effects for the individual cases, but also to estimate and test the overall effect, and explore the generality of this effect across cases and under different conditions. (Contains 2 figures and 1 table.)