Evidence map›Paper›PMID 33660923›Full record

ArticleHuman brain mapping2021

Improving the replicability of neuroimaging findings by thresholding effect sizes instead of p-values.

Simon N Vandekar, Jeremy Stephens

Abstract read
In one paragraph

Article in Human brain mapping, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 2 pooled it
–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

11 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Reconfiguration of brain-wide neural activity after early life adversity.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  5. Article
  6. Reconfiguration of brain-wide neural activity after early life adversity.bioRxiv : the preprint server for biology · 2025
    Article
  7. Article
  8. Article
  9. Article
  10. Observational
  11. 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

2 authors.

Simon N VandekarDepartment of Biostatistics, Vanderbilt University, Nashville, Tennessee, USA.ORCID 0000-0002-7457-9073
Jeremy StephensDepartment of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee, USA.

Funding

Tumor Immunology and Microenvironment Research ProgramP30CA068485 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI MATTHEW J TYSKA · 1995 to 2026
$172.8M
Vanderbilt-Ingram Cancer Center SPORE in Gastrointestinal CancerP50CA236733 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI STEPHEN W. FESIK · 2019 to 2026
$19.6M
Semiparametric Inference for Psychiatric NeuroimagingR01MH123563 · NIMH · VANDERBILT UNIVERSITY MEDICAL CENTER · PI VANDEKAR, SIMON NEIL · 2020 to 2024
$2.1M
NCI NIH HHS P30 CA068485NCI NIH HHS P50 CA236733NCI NIH HHS P50CA236733NIMH NIH HHS 1R01MH123563-01NIMH NIH HHS R01 MH123563
6 · The paper itself

Abstract

The classical approach for testing statistical images using spatial extent inference (SEI) thresholds the statistical image based on the p-value. This approach has an unfortunate consequence on the replicability of neuroimaging findings because the targeted brain regions are affected by the sample size-larger studies have more power to detect smaller effects. Here, we use simulations based on the preprocessed Autism Brain Imaging Data Exchange (ABIDE) to show that thresholding statistical images by effect sizes has more consistent estimates of activated regions across studies than thresholding by p-values. Using a constant effect size threshold means that the p-value threshold naturally scales with the sample size to ensure that the target set is similar across repetitions of the study that use different sample sizes. As a consequence of thresholding by the effect size, the type 1 and type 2 error rates go to zero as the sample size gets larger. We use a newly proposed robust effect size index that is defined for an arbitrary statistical image so that effect size thresholding can be used regardless of the test statistic or model.

Indexed as

Data Interpretation, StatisticalBrainHumansImage Processing, Computer-AssistedNeuroimagingReproducibility of ResultsABIDEcluster extent inferencerobust effect size index

Identifiers

PMID33660923
PMCPMC8090771

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

None linked

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.