Deciding what to replicate: A decision model for replication study selection under resource and knowledge constraints.


Journal

Psychological methods
ISSN: 1939-1463
Titre abrégé: Psychol Methods
Pays: United States
ID NLM: 9606928

Informations de publication

Date de publication:
Apr 2023
Historique:
medline: 15 5 2023
pubmed: 21 12 2021
entrez: 20 12 2021
Statut: ppublish

Résumé

Robust scientific knowledge is contingent upon replication of original findings. However, replicating researchers are constrained by resources, and will almost always have to choose one replication effort to focus on from a set of potential candidates. To select a candidate efficiently in these cases, we need methods for deciding which out of all candidates considered would be the most useful to replicate, given some overall goal researchers wish to achieve. In this article we assume that the overall goal researchers wish to achieve is to maximize the utility gained by conducting the replication study. We then propose a general rule for study selection in replication research based on the

Identifiants

pubmed: 34928679
pii: 2022-14587-001
doi: 10.1037/met0000438
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

438-451

Auteurs

Peder Mortvedt Isager (PM)

Department of Industrial Engineering and Innovation Sciences, Eindhoven University of Technology.

Robbie C M van Aert (RCM)

Department of Methodology and Statistics, Tilburg University.

Štěpán Bahník (Š)

Department of Management, Faculty of Business Administration, Prague University of Economics and Business.

Mark J Brandt (MJ)

Department of Social Psychology, Tilburg University.

K Andrew DeSoto (KA)

Association for Psychological Science.

Roger Giner-Sorolla (R)

School of Psychology, University of Kent.

Joachim I Krueger (JI)

Department of Cognitive, Linguistic and Psychological Sciences, Brown University.

Marco Perugini (M)

Department of Psychology, University of Milano-Bicocca.

Ivan Ropovik (I)

Faculty of Education, Charles University.

Anna E van 't Veer (AE)

Methodology and Statistics Unit, Institute of Psychology, Leiden University.

Marek Vranka (M)

Faculty of Social Sciences, Charles University.

Daniël Lakens (D)

Department of Industrial Engineering and Innovation Sciences, Eindhoven University of Technology.

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Classifications MeSH