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

• Daniela Alvarez-Vargas ,

  Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Validation, Visualization, Writing – original draft, Writing – review & editing

  * E-mail: dalvare5@uci.edu

  Affiliation School of Education, University of California, Irvine, Irvine, California, United States of America

  https://orcid.org/0000-0002-4075-1154

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• David Braithwaite,

  Roles Conceptualization, Data curation, Methodology, Project administration, Supervision, Validation, Writing – review & editing

  Affiliation Department of Psychology, Florida State University, Tallahassee, Florida, United States of America

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• Hugues Lortie-Forgues,

  Roles Conceptualization, Data curation, Methodology, Supervision, Validation, Writing – review & editing

  Affiliation Department of Mathematics Education, Loughborough University, Loughborough, Leicestershire, United Kingdom

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• Melody Moore,

  Roles Conceptualization, Writing – review & editing

  Affiliation Department of Psychology, Baylor University, Waco, Texas, United States of America

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• Sirui Wan,

  Roles Conceptualization, Methodology, Writing – review & editing

  Affiliation Department of Psychology at the University of Wisconsin-Madison, Madison, Wisconsin, United States of America

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• Elizabeth Martin,

  Roles Methodology, Writing – review & editing

  Affiliation Department of Psychological Science, University of California, Irvine, Irvine, California, United States of America

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• Drew Hal Bailey

  Roles Conceptualization, Data curation, Methodology, Project administration, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

  Affiliation Department of Psychological Science, University of California, Irvine, Irvine, California, United States of America

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