2021
DOI: 10.3390/ijerph18179304
|View full text |Cite
|
Sign up to set email alerts
|

Multiplicity Eludes Peer Review: The Case of COVID-19 Research

Abstract: Multiplicity arises when data analysis involves multiple simultaneous inferences, increasing the chance of spurious findings. It is a widespread problem frequently ignored by researchers. In this paper, we perform an exploratory analysis of the Web of Science database for COVID-19 observational studies. We examined 100 top-cited COVID-19 peer-reviewed articles based on p-values, including up to 7100 simultaneous tests, with 50% including >34 tests, and 20% > 100 tests. We found that the larger the number… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1

Citation Types

0
3
0

Year Published

2022
2022
2025
2025

Publication Types

Select...
4
1

Relationship

0
5

Authors

Journals

citations
Cited by 5 publications
(3 citation statements)
references
References 33 publications
0
3
0
Order By: Relevance
“… 28 , 33 , 34 , 35 As the pandemic has progressed and COVID-19 has become global, the robustness of early studies suggesting strong links between climate and COVID-19 have been questioned. 33 , 34 , 47 , 54 , 55 Reviewing these studies, Gutiérrez-Hernández and García 34 argue that evidence of climate influences on COVID-19 is not robust enough to be considered in public health policies.…”
Section: Climatic Risks Influencing the Transmission Of Covid-19mentioning
confidence: 99%
“… 28 , 33 , 34 , 35 As the pandemic has progressed and COVID-19 has become global, the robustness of early studies suggesting strong links between climate and COVID-19 have been questioned. 33 , 34 , 47 , 54 , 55 Reviewing these studies, Gutiérrez-Hernández and García 34 argue that evidence of climate influences on COVID-19 is not robust enough to be considered in public health policies.…”
Section: Climatic Risks Influencing the Transmission Of Covid-19mentioning
confidence: 99%
“…The second factor is inherent to the research process and may be defined as “the multiplicity bias”. Recently, in fact, Gutiérrez-Hernández and García ( 2021b ) pointed out how observational studies in COVID-19 correlation tests research risk to be affected by a much greater number of type I errors than what is generally believed. This should not discourage a pragmatic epidemiological geography in its effort to build up coherent and consistent overviews (Kundi, 2006 ).…”
Section: Discussionmentioning
confidence: 99%
“…The number of papers circulating in the second half of 2020 was likely to be underestimated, because paper indexing in search engines may require long time to become effective. Finally, it cannot be excluded that the number of papers not finding any relevant correlation among the covariates was underestimated because of the “publication bias” (Gutiérrez-Hernández, 2021b ). Future research should consider that the geographers’ toolkit, constituted by GIS, statistical analysis and geostatistics may be fruitfully applied in spatial analysis of infectious diseases, but with the highest possible awareness about the fundaments of epidemiology.…”
Section: Conclusion Limitations and Further Developmentsmentioning
confidence: 99%