Evidence map›Paper›PMID 39226265›Full record

ArticlePloS one2024

A citation analysis of (f)MRI papers that cited Lieberman and Cunningham (2009) to justify their statistical threshold.

Andy Wai Kan Yeung

Abstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Andy Wai Kan YeungOral and Maxillofacial Radiology, Applied Oral Sciences and Community Dental Care, Faculty of Dentistry, The University of Hong Kong, Hong Kong, China.ORCID 0000-0003-3672-357X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionIn current neuroimaging studies, the mainstream practice is to report results corrected for multiple comparisons to control for false positives. In 2009, Lieberman and Cunningham published a highly cited report that promotes the use of uncorrected statistical thresholds to balance Types I and II error rates. This paper aims to review recent studies that cited this report, investigating whether the citations were to justify the use of uncorrected statistical thresholds, and if their uncorrected thresholds adhered to the recommended defaults.

methodsThe Web of Science Core Collection online database was queried to identify original articles published during 2019-2022 that cited the report.

resultsIt was found that the majority of the citing papers (152/225, 67.6%) used the citation to justify their statistical threshold setting. However, only 19.7% of these 152 papers strictly followed the recommended uncorrected P (Punc) < 0.005, k = 10 (15/152, 9.9%) or Punc < 0.005, k = 20 (15/152, 9.9%). Over half (78/152, 51.3%) used various cluster-extent based thresholds with Punc, with the predominant choices being Punc < 0.001, k = 50 and Punc < 0.001, k = 10, mostly without justifying their deviation from the default. Few papers matched the voxel size and smoothing kernel size used by the simulations from the report to derive the recommended thresholds.

conclusionThis survey reveals a disconnect between the use and citation of Lieberman and Cunningham's report. Future studies should justify their chosen statistical thresholds based on rigorous statistical theory and study-specific parameters, rather than merely citing previous works. Furthermore, this paper encourages the neuroimaging community to publicly share their group-level statistical images and metadata to promote transparency and collaboration.

Indexed as

Magnetic Resonance ImagingHumansNeuroimaging

Identifiers

PMID39226265
PMCPMC11371206

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.