Comparing Visual and Statistical Analysis in Single-Case Studies Using Published Studies

Harrington, Magadalena; Velicer, Wayne F.

doi:10.1080/00273171.2014.973989

Cited by 114Behavioral and Psychological StudiesMeta-analysis and systematic reviewsStatistical Methods and Bayesian Inference

Comparing Visual and Statistical Analysis in Single-Case Studies Using Published Studies

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Harrington, Magadalena, Velicer, Wayne F.·2015·Multivariate Behavioral Research

DOI 10.1080/00273171.2014.973989PMC PMC4677800

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Abstract

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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There can be disagreement between raters on whether change is present in visual analysis.
“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
Inter-rater agreement is often low in visual analysis.
“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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Comparing Visual and Statistical Analysis in Single-Subject Studies
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Self-citation
INTERRUPTED TIME‐SERIES ANALYSIS AND ITS APPLICATION TO BEHAVIORAL DATA
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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
DOI: 10.1080/00273171.2014.973989
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 · 2014: 1
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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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

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Comparing Visual and Statistical Analysis in Single-Case Studies Using Published Studies

Abstract

Integrity signals

Claims the paper makes

Claims other papers make about this one

Self-check

Cites

Cited by

Related

Record

About these checks