Year: 2025
Type: article
Abstract: Visual analysis is a primary method for analyzing data obtained from single-case experimental designs (SCEDs). Traditionally, visual analysis of SCED data involves the inspection of time-series data depicting the dependent variable under the different experimental conditions over time. While various guidelines and visual aids have been developed to improve transparency, standardization, and ultimately the rigor of visually analyzing SCED time-series data, reliability issues still pertain. In addition, the scope of information that can be gathered by visually analyzing the raw time-series data is limited. For these reasons, visual analysis of SCED time-series data should be complemented by statistical as well as alternative visual analytical methods. In this article, we give an overview of some alternative visual analytical methods applicable to SCEDs: modified Brinley plots, extended modified Brinley plots, and violin plots. We outline the scope of applicability of each plot type, explain how to interpret them, and review their relative strengths and weaknesses. Resources in the form of freely available Shiny apps and R-code for easily constructing each plot type are provided.
Authors: René Tanious, Rumen Manolov
Institutions: Maastricht University, Universitat de Barcelona
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4408012962