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Comparing Visual and Statistical Analysis in Single-Case Studies Using Published Studies
Open accessAbstract
Little is known about the extent to which interrupted time series analysis (ITSA) can be applied to short, single-case study designs and whether those applications produce results consistent with visual analysis (VA). This article examines the extent to which ITSA can be applied to single-case study designs and compares the results based on two methods: ITSA and VA, using papers published in the Journal of Applied Behavior Analysis in 2010. The study was made possible by the development of software called UnGraph®, which facilitates the recovery of raw data from the graphs. ITSA was successfully applied to 94% of the examined graphs with the number of observations ranging from 8 to 136. Moderate to high lag-1 autocorrelations (>.50) were found for 46% of the data series. Effect sizes similar to group-level Cohen's d were identified based on the tertile distribution. Effects ranging from 0.00 to 0.99 were classified as small, those ranging from 1.00 to 2.49 as medium, and large effect sizes were defined as 2.50 or greater. Comparison of the conclusions from VA and ITSA had a low level of agreement (Kappa =.14, accounting for the agreement expected by chance). The results demonstrate that ITSA can be broadly implemented in applied behavior analysis research. These two methods should be viewed as complementary and used concurrently.
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“For example, there can be disagreement between raters on whether change is present; therefore, inter-rater agreement often low in visual analysis (Harrington & Velicer, 2015).”
From A pilot case series of a brief acceptance and commitment therapy (ACT)-based guided self-help intervention for improving quality of life and mood in muscle disorders (2017) · cites this paper as Harrington & Velicer, 2015
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“therefore, inter-rater agreement often low in visual analysis (Harrington & Velicer, 2015).”
From A pilot case series of a brief acceptance and commitment therapy (ACT)-based guided self-help intervention for improving quality of life and mood in muscle disorders (2017) · cites this paper as Harrington & Velicer, 2015
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Citations
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A Tribute to the Mind, Methodology and Mentoring of Wayne Velicer
Harlow, L. L., Aiken, L. S., Blankson, A. N., Boodoo, G. M., Brick, L. A. D., Collins, L. M., Cumming, G., Fava, J. L., Goodwin, M. S., Hoeppner, B. B., et al. (2020) · Multivariate Behavioral Research · doi:10.1080/00273171.2020.1729083
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Metadata
- Authors
- Harrington, M., & Velicer, W. F.
- Affiliations
- University of Rhode Island (US)
- Corresponding author
- Velicer, Wayne F.
- ORCID
- Velicer, Wayne F.
- Venue
- Multivariate Behavioral Research
- Publisher
- Informa UK Limited
- Published
- 2015-03-04
- Volume
- 50
- Issue
- 2
- Pages
- 162-183
- ISSN
- 0027-3171 (ISSN-L)
- 1532-7906
- PMC
- PMC4677800
- OpenAlex
- W1969454087
- Cited by
- 114
- References
- 80
- Citations by year
- 2026: 2 · 2025: 7 · 2024: 14 · 2023: 9 · 2022: 18 · 2021: 18 · 2020: 16 · 2019: 6 · 2018: 7 · 2017: 10 · 2016: 6
- FWCI
- 19.39
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Multivariate Behavioral Research (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Journal of Media Literacy Education (submittedVersion, cc-by)
- Funders
- National Institute on Drug Abuse (R01DA020112, DA020112)
- Topics
- Social Sciences › Psychology › Developmental and Educational Psychology › Behavioral and Psychological Studies
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Keywords
- interrupted time series, visual analysis, single-case experimental design, autocorrelation, effect size, applied behavior analysis, measurement agreement
- MeSH terms
- Humans, Research Design, Reproducibility of Results, Behavioral Research, Interrupted Time Series Analysis
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