Assessing Nonoverlap in Single-Case Data: Strengths Challenges and Recommendations
Overlap 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...
| Autores: | , |
|---|---|
| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2024 |
| País: | España |
| Institución: | Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya) |
| Repositorio: | Recercat. Dipósit de la Recerca de Catalunya |
| OAI Identifier: | oai:recercat.cat:2445/224274 |
| Acceso en línea: | https://hdl.handle.net/2445/224274 |
| Access Level: | acceso abierto |
| Palabra clave: | Disseny d'experiments Investigació quantitativa Experimental design Quantitative research |
| Sumario: | Overlap 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 SCEDs |
|---|