Single-case experimental designs entail the intensive study of one or few entities (e.g., individuals) in different conditions, which are manipulated by the researchers. Some designs include intra-subject replication (ABAB design, changing criterion design, and alternating treatments design), whereas the multiple-baseline design usually includes between-subjects replication. For both scenarios, there are several attempts to demonstrate the intervention effect (introducing or withdrawing the intervention) in different moments in time. Moreover, the replication of the results in different studies is necessary for establishing the generality of the conclusions. Regarding data analysis, there are currently multiple proposals, without a consensus regarding which the optimal analytical techniques are. In order to make easier the necessary justification of any data analytical technique chosen, the current text offers a series of organizing principles, which indicate in which situation each of the options is most useful. Furthermore, in order to bring applied researchers closer to the analytical options, the text refers to freely accessible websites implementing them. Finally, given that it is not possible to discuss in detail all methodological aspects, or to review all available data analytical techniques, the interested reader is directed via multiple references to the primary sources.
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