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The P value plot does not provide evidence against air pollution hazards

A number of papers by Young and collaborators have criticized epidemiological studies and meta-analyses of air pollution hazards using a graphical method that the authors call a P value plot, claiming to find zero effects, heterogeneity, and P hacking. However, the P value plot method has not been v...

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Detalles Bibliográficos
Autor principal: Hicks, Daniel J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9005255/
https://www.ncbi.nlm.nih.gov/pubmed/35434466
http://dx.doi.org/10.1097/EE9.0000000000000198
Descripción
Sumario:A number of papers by Young and collaborators have criticized epidemiological studies and meta-analyses of air pollution hazards using a graphical method that the authors call a P value plot, claiming to find zero effects, heterogeneity, and P hacking. However, the P value plot method has not been validated in a peer-reviewed publication. The aim of this study was to investigate the statistical and evidentiary properties of this method. METHODS: A simulation was developed to create studies and meta-analyses with known real effects [Formula: see text] , integrating two quantifiable conceptions of evidence from the philosophy of science literature. The simulation and analysis is publicly available and automatically reproduced. RESULTS: In this simulation, the plot did not provide evidence for heterogeneity or P hacking with respect to any condition. Under the right conditions, the plot can provide evidence of zero effects; but these conditions are not satisfied in any actual use by Young and collaborators. CONCLUSION: The P value plot does not provide evidence to support the skeptical claims about air pollution hazards made by Young and collaborators.