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The intriguing evolution of effect sizes in biomedical research over time: smaller but more often statistically significant
Author(s) -
Paul Monsarrat,
JeanNoël Vergnes
Publication year - 2017
Publication title -
gigascience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.947
H-Index - 54
ISSN - 2047-217X
DOI - 10.1093/gigascience/gix121
Subject(s) - computer science , data science , computational biology , biology
In medicine, effect sizes (ESs) allow the effects of independent variables (including risk/protective factors or treatment interventions) on dependent variables (e.g., health outcomes) to be quantified. Given that many public health decisions and health care policies are based on ES estimates, it is important to assess how ESs are used in the biomedical literature and to investigate potential trends in their reporting over time.

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