Hedges, mottes, and baileys: Causally ambiguous statistical language can increase perceived study quality and policy relevance

Bibliográfalaš dieđut
Váldodahkkit:	Daniela Alvarez-Vargas, David Braithwaite, Hugues Lortie-Forgues, Melody Moore, Sirui Wan, Elizabeth Martin, Drew Hal Bailey
Materiálatiipa:	Artihkal
Giella:	English
Almmustuhtton:	Public Library of Science (PLoS) 2023-01-01
Ráidu:	PLoS ONE
Liŋkkat:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10602341/?tool=EBI

Hedges, mottes, and baileys: Causally ambiguous statistical language can increase perceived study quality and policy relevance. Dahkki Daniela Alvarez-Vargas, David Braithwaite, Hugues Lortie-Forgues, Melody Moore, Sirui Wan, Elizabeth Martin, Drew Hal Bailey

Almmustuhtton 2023-01-01

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