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Examination of CIs in health and medical journals from 1976 to 2019: an observational study

OBJECTIVES: Previous research has shown clear biases in the distribution of published p values, with an excess below the 0.05 threshold due to a combination of p-hacking and publication bias. We aimed to examine the bias for statistical significance using published confidence intervals. DESIGN: Obse...

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Detalles Bibliográficos
Autores principales: Barnett, Adrian Gerard, Wren, Jonathan D
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6887056/
https://www.ncbi.nlm.nih.gov/pubmed/31753893
http://dx.doi.org/10.1136/bmjopen-2019-032506
Descripción
Sumario:OBJECTIVES: Previous research has shown clear biases in the distribution of published p values, with an excess below the 0.05 threshold due to a combination of p-hacking and publication bias. We aimed to examine the bias for statistical significance using published confidence intervals. DESIGN: Observational study. SETTING: Papers published in Medline since 1976. PARTICIPANTS: Over 968 000 confidence intervals extracted from abstracts and over 350 000 intervals extracted from the full-text. OUTCOME MEASURES: Cumulative distributions of lower and upper confidence interval limits for ratio estimates. RESULTS: We found an excess of statistically significant results with a glut of lower intervals just above one and upper intervals just below 1. These excesses have not improved in recent years. The excesses did not appear in a set of over 100 000 confidence intervals that were not subject to p-hacking or publication bias. CONCLUSIONS: The huge excesses of published confidence intervals that are just below the statistically significant threshold are not statistically plausible. Large improvements in research practice are needed to provide more results that better reflect the truth.