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

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

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There is a norm in psychology to use causally ambiguous statistical language, rather than straightforward causal language, when describing methods and results of nonexperimental studies. However, causally ambiguous language may inhibit a critical examination of the study's causal assumptions an...

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Bibliographic Details
Main Authors: Daniela Alvarez-Vargas, David Braithwaite, Hugues Lortie-Forgues, Melody Moore, Sirui Wan, Elizabeth Martin, Drew Hal Bailey
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2023-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0286403

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https://doi.org/10.1371/journal.pone.0286403

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