A Priori Justification for Effect Measures in Single-Case Experimental Designs.

quantitative methods reporting standards scientific rigor single-case experimental design statistical analysis

Journal

Perspectives on behavior science
ISSN: 2520-8977
Titre abrégé: Perspect Behav Sci
Pays: Switzerland
ID NLM: 101743058

Informations de publication

Date de publication:
Mar 2022
Historique:
accepted: 27 01 2021
entrez: 28 3 2022
pubmed: 29 3 2022
medline: 29 3 2022
Statut: epublish

Résumé

Due to the complex nature of single-case experimental design data, numerous effect measures are available to quantify and evaluate the effectiveness of an intervention. An inappropriate choice of the effect measure can result in a misrepresentation of the intervention effectiveness and this can have far-reaching implications for theory, practice, and policymaking. As guidelines for reporting appropriate justification for selecting an effect measure are missing, the first aim is to identify the relevant dimensions for effect measure selection and justification prior to data gathering. The second aim is to use these dimensions to construct a user-friendly flowchart or decision tree guiding applied researchers in this process. The use of the flowchart is illustrated in the context of a preregistered protocol. This is the first study that attempts to propose reporting guidelines to justify the effect measure choice, before collecting the data, to avoid selective reporting of the largest quantifications of an effect. A proper justification, less prone to confirmation bias, and transparent and explicit reporting can enhance the credibility of the single-case design study findings.

Identifiants

pubmed: 35342872
doi: 10.1007/s40614-021-00282-2
pii: 282
pmc: PMC8894525
doi:

Types de publication

Journal Article

Langues

eng

Pagination

153-186

Informations de copyright

© Association for Behavior Analysis International 2021.

Déclaration de conflit d'intérêts

Conflicts of interest/Competing interestsThe authors report no conflicts of interest But the underlying code for creating these application is not been publicly shared in the context of the current manuscript.

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Auteurs

Rumen Manolov (R)

Department de Psicologia Social i Psicologia Quantitativa, Universitat de Barcelona, Passeig de la Vall d´Hebron 171, 08035 Barcelona, Spain.

Mariola Moeyaert (M)

State University of New York at Albany, Albany, NY USA.

Joelle E Fingerhut (JE)

State University of New York at Albany, Albany, NY USA.

Classifications MeSH