Which variables should be controlled for to investigate picture naming in adults? A Bayesian meta-analysis.


Journal

Behavior research methods
ISSN: 1554-3528
Titre abrégé: Behav Res Methods
Pays: United States
ID NLM: 101244316

Informations de publication

Date de publication:
12 2019
Historique:
pubmed: 2 8 2018
medline: 29 2 2020
entrez: 2 8 2018
Statut: ppublish

Résumé

Selecting items for designing psycholinguistic experiments can be a very hard and time-consuming process, because of the large number of variables that need to be controlled for. This is clearly the case for picture-naming experiments because, thanks to the collection of psycholinguistic norms on both pictures and their names, a large number of factors that affect naming speed and/or accuracy have been found. In the present study, a Bayesian meta-analysis was performed to determine the extent to which the variables that have generally been considered by researchers as important to control for are indeed worth taking into account. The meta-analysis revealed that most of the variables that are considered in picture-naming studies have a strong or very strong influence on naming speed (image agreement, name agreement, image variability/imageability, age of acquisition, and conceptual familiarity), whereas two variables that are very often taken into account (visual complexity and length) yielded null effects. The results were inconclusive for lexical frequency. At a methodological level, Bayesian meta-analyses constitute a very useful tool for guiding researchers when selecting materials for experiments.

Identifiants

pubmed: 30066263
doi: 10.3758/s13428-018-1100-1
pii: 10.3758/s13428-018-1100-1
doi:

Types de publication

Journal Article Meta-Analysis Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

2533-2545

Auteurs

Cyril Perret (C)

Université de Poitiers, Université de Tours, CNRS, 5, rue Théodore Lefebvre, TSA 21103, 86073, Poitiers Cedex 9, France. cyril.perret@univ-poitiers.fr.

Patrick Bonin (P)

Université de Bourgogne, CNRS, Franche-Comté, France.

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Classifications MeSH