Visual Analysis of Single-Case Experimental Designs Data: Beyond Time-Series Graphs

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.

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Institutions

Publication Details

Journal
Single Case in the Social Sciences
Published
2025-02-26
DOI
https://doi.org/10.15763/issn.1936-9298.2025.2.1.43-64
Citations
4
Primary Topic
Behavioral and Psychological Studies
Type
article
Field-Weighted Citation Impact
13.78

Funders

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article

Visual Analysis of Single-Case Experimental Designs Data: Beyond Time-Series Graphs

René Tanious, Rumen Manolov
4 citations
Single Case in the Social Sciences
Behavioral and Psychological Studies
13.78
article

Visual Analysis of Single-Case Experimental Designs Data: Beyond Time-Series Graphs

René Tanious, Rumen Manolov
article en
4 citations

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.

Single Case in the Social SciencesVol. 2(1)
Maastricht University (NL), Universitat de Barcelona (ES)
Generalitat de Catalunya, Nederlandse Organisatie voor Wetenschappelijk Onderzoek
Openalex Percentile: Top 2%
Behavioral and Psychological Studies
13.78
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