Selecting and justifying quantitative analysis techniques in single-case research through a user-friendly open-source tool

Abstract

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Certain quantification techniques may be more appropriate than others for single-case design analysis depending on the research questions, the data or graph characteristics, and other desired features. The purpose of this study was to introduce a newly developed and empirically validated user-friendly tool to assist researchers in choosing and justifying single-case design quantification techniques. A total of sixteen different quantification techniques and nine facets (research questions, data or graph characteristics, or desired features) that may affect the appropriateness of a single-case experimental design quantification technique were identified to be included in the tool. The resulting tool provides a ranking of recommended quantification techniques, from most to least appropriate, depending on the user input. A pretest and posttest design was utilized to test the effectiveness of the tool amongst 25 participants. The findings revealed that those who use single-case designs may need support in choosing and justifying their use of quantification techniques. Those who utilize single-case designs should use the developed tool (and other tools) to assist with their analyses. The open-source tool can be downloaded from osf.io/7usbj/.

Keywords

• single-case design
• quantification techniques
• evidence-based
• open-source tool
• decision-making
• applied behavior analysis