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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...
Autor principal: | |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2022
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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 |
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. |
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