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Effect Size in Single-Case Research

A Review of Nine Nonoverlap Techniques

Bibliographic Data

ID23323832
AuthorsRichard I Parker (Texas A&M University, College Station,, corresponding author), Kimberly J Vannest (0000-0002-2285-0837, Texas A&M University, College Station), John L Davis (0000-0002-4394-2503, Texas A&M University, College Station)
Year2011
Volume35
Issue4
Pages303-322
Publication date2011-07-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueBehavior Modification (JOURNAL)
Journal identifiersISSN: 0145-4455 • E-ISSN: 1552-4167
PublisherSAGE Publications (PUBLISHER • US)
DOI10.1177/0145445511399147
PMID21411481
OpenAlexW2019951734
LanguageEN
Citations received53
References cited36

With rapid advances in the analysis of data from single-case research designs, the various behavior-change indices, that is, effect sizes, can be confusing. To reduce this confusion, nine effect-size indices are described and compared. Each of these indices examines data nonoverlap between phases. Similarities and differences, both conceptual and computational, are highlighted. Seven of the nine indices are applied to a sample of 200 published time series data sets, to examine their distributions. A generic meta-analytic method is presented for combining nonoverlap indices across multiple data series within complex designs.

Confusion · Data mining · Econometrics · Sample (material) · Sample size determination · Series (stratigraphy) · Statistics · Behavioral and Psychological Studies · Computer Science · Mathematics · Optimal Experimental Design Methods · Psychology

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Unique citing works53
Citations per year3,79
Citation span2012 - 2026 (15)
Citation velocitycurrent
Highly citedNo
Citation typesNeutral: 51

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