Manolov, RumenTanious, René2025-11-112025-11-112024-06-191053-0819https://hdl.handle.net/2445/224274Overlap is one of the data aspects that are expected to be assessed when visually inspecting single-case experimental designs (SCED) data. A frequently used quanti- fication of overlap is the Nonoverlap of All Pairs (NAP). The current article reviews the main strengths and challenges when using this index, as compared to other nono- verlap indices such as Tau and the Percentage of data points exceeding the median. Four challenges are reviewed: the difficulty in representing NAP graphically, the presence of a ceiling effect, the disregard of trend, and the limitations in using p-values associated with NAP. Given the importance of complementing quantitative analysis and visual inspection of graphed data, straightforward quantifications and new graphical elements for the time-series plot are proposed as options for address- ing the first three challenges. The suggestions for graphical representations (repre- senting within-phase monotonic trend and across-phases overlaps) and additional numerical summaries (quantifying the degree of separation in case of complete non- overlap or the proportion of data points in the overlap zone) are illustrated with two multiple-baseline data sets. To make it easier to obtain the plots and quantifications, the recommendations are implemented in a freely available user-friendly website. Educational researchers can use this article to inform their use and application of NAP to meaningfully interpret this quantification in the context of SCEDs33 p.application/pdfengcc-by-nc-nd (c) Manolov Rumen et al., 2024http://creativecommons.org/licenses/by-nc-nd/4.0/Disseny d'experimentsInvestigació quantitativaExperimental designQuantitative researchAssessing Nonoverlap in Single-Case Data: Strengths Challenges and Recommendationsinfo:eu-repo/semantics/publishedVersion7511442025-11-11info:eu-repo/semantics/openAccess