ArticleNeuroImage2021
Confidence Sets for Cohen's d effect size images.
Article in NeuroImage, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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.
Who cites it
27 citing papers in PubMed, 1 synthesis or guideline pooled it.
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- Effect sizes in human functional neuroimaging.Research square · 2026Article
- The Hidden Landscape of Missed Effects in Human Functional Neuroimaging.bioRxiv : the preprint server for biology · 2026Article
- SPM-30 years and beyond.Cerebral cortex (New York, N.Y. : 1991) · 2025Review
- Intermittent Fasting Enhances Motor Coordination Through Myelin Preservation in Aged Mice.Aging cell · 2025Article
- Semiparametric confidence sets for cross-sectional and longitudinal neuroimaging.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Effects and mechanisms of a home-based action observation and motor imagery intervention on cognitive function and depression in spinal cord injury: a pilot randomized controlled trial protocol.Frontiers in neurology · 2025Article
- Perceptions and attitudes of South African physiotherapists towards National Health Insurance.Health SA = SA Gesondheid · 2025Article
- Bayesian inference for group-level cortical surface image-on-scalar regression with Gaussian process priors.Biometrics · 2024Article
- Inverse set estimation and inversion of simultaneous confidence intervals.Journal of the Royal Statistical Society. Series C, Applied statistics · 2024Article
- Applicability of the Cumberland Ankle Instability Tool in Elite Volleyball Athletes: A Cross-Sectional Observational Study.Sports (Basel, Switzerland) · 2024Article
- Spatial confidence regions for combinations of excursion sets in image analysis.Journal of the Royal Statistical Society. Series B, Statistical methodology · 2024Article
- Topological cluster statistic (TCS): Toward structural connectivity-guided fMRI cluster enhancement.Network neuroscience (Cambridge, Mass.) · 2024Article
- Effects of Cycling on Spine: A Case-Control Study Using a 3D Scanning Method.Sports (Basel, Switzerland) · 2023Article
- Orofacial Myofunctional Aspects of Nursing Infants and Preschoolers.International archives of otorhinolaryngology · 2023Article
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- Comparison of the Effects of Superficial and Deep Heat Agents on Hamstring Muscle Flexibility in Healthy Individuals.Journal of clinical practice and research · 2023Article
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- Functional delta residuals and applications to simultaneous confidence bands of moment based statistics.Journal of multivariate analysis · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Current statistical inference methods for task-fMRI suffer from two fundamental limitations. First, the focus is solely on detection of non-zero signal or signal change, a problem that is exacerbated for large scale studies (e.g. UK Biobank, N=40,000+) where the 'null hypothesis fallacy' causes even trivial effects to be determined as significant. Second, for any sample size, widely used cluster inference methods only indicate regions where a null hypothesis can be rejected, without providing any notion of spatial uncertainty about the activation. In this work, we address these issues by developing spatial Confidence Sets (CSs) on clusters found in thresholded Cohen's d effect size images. We produce an upper and lower CS to make confidence statements about brain regions where Cohen's d effect sizes have exceeded and fallen short of a non-zero threshold, respectively. The CSs convey information about the magnitude and reliability of effect sizes that is usually given separately in a t-statistic and effect estimate map. We expand the theory developed in our previous work on CSs for %BOLD change effect maps (Bowring et al., 2019) using recent results from the bootstrapping literature. By assessing the empirical coverage with 2D and 3D Monte Carlo simulations resembling fMRI data, we find our method is accurate in sample sizes as low as N=60. We compute Cohen's d CSs for the Human Connectome Project working memory task-fMRI data, illustrating the brain regions with a reliable Cohen's d response for a given threshold. By comparing the CSs with results obtained from a traditional statistical voxelwise inference, we highlight the improvement in activation localization that can be gained with the Confidence Sets.
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Registered trials
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.