ArticleNeuroImage2015
Multi-level block permutation.
Article in NeuroImage, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 168 papers.
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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.
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Who cites it
168 citing papers in PubMed, 276 citations in OpenAlex.
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- Replication of Resting State-Task Network Correspondence and Novel Findings on Brain Network Activation During Task fMRI in the Human Connectome Project Study.Scientific reports · 2018Trial
- Article
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- Brain morphometry patterns in the presence of Alzheimer's disease and/or LATE neuropathologic changes.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- A comprehensive framework for statistical testing of brain dynamics.Nature protocols · 2026Review
- The intrinsic cortical geometry of reading.bioRxiv : the preprint server for biology · 2026Article
- Associations of stable psychological traits with multi-omic subtypes of Alzheimer's dementia.Translational psychiatry · 2026Article
- Brain age prediction in generalized anxiety disorder using a convolutional neural network.Translational psychiatry · 2026Article
- Functional Magnetic Resonance Imaging Signal Typically Viewed as "Noise" Has Clinical Relevance in Psychiatry.Biological psychiatry global open science · 2026Article
- ADHD symptom trajectories and brain morphometry: A longitudinal analysis.medRxiv : the preprint server for health sciences · 2026Article
- Testing for Network Specificity in Brain-Behavior Associations Using Ordinal Dominance Curves.Human brain mapping · 2026Article
- Genetic parallelism underpins convergent mimicry coloration in Lepidoptera across 120 million years of evolution.PLoS biology · 2026Article
- singIST: An integrative method for comparative single-cell transcriptomics between disease models and humans.PLoS computational biology · 2026Article
- Bias in Structural MRI Correlates of Delay Discounting due to Head Motion.Human brain mapping · 2026Article
- Calibrating and documenting host-switching and evolution of incompatibility loci for two closely relatedbioRxiv : the preprint server for biology · 2026Article
- Map-like representations of emotion knowledge in hippocampal-prefrontal systems.Nature communications · 2026Article
- Structural brain changes in the development of essential tremor: toward early diagnosis.Frontiers in aging neuroscience · 2026Article
- Auditory and Visual Thalamocortical Connectivity Alterations in Unmedicated People With Schizophrenia: An Individualized Sensory Thalamic Localization and Resting-State Functional Connectivity Study.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2025Article
108 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
Under weak and reasonable assumptions, mainly that data are exchangeable under the null hypothesis, permutation tests can provide exact control of false positives and allow the use of various non-standard statistics. There are, however, various common examples in which global exchangeability can be violated, including paired tests, tests that involve repeated measurements, tests in which subjects are relatives (members of pedigrees) - any dataset with known dependence among observations. In these cases, some permutations, if performed, would create data that would not possess the original dependence structure, and thus, should not be used to construct the reference (null) distribution. To allow permutation inference in such cases, we test the null hypothesis using only a subset of all otherwise possible permutations, i.e., using only the rearrangements of the data that respect exchangeability, thus retaining the original joint distribution unaltered. In a previous study, we defined exchangeability for blocks of data, as opposed to each datum individually, then allowing permutations to happen within block, or the blocks as a whole to be permuted. Here we extend that notion to allow blocks to be nested, in a hierarchical, multi-level definition. We do not explicitly model the degree of dependence between observations, only the lack of independence; the dependence is implicitly accounted for by the hierarchy and by the permutation scheme. The strategy is compatible with heteroscedasticity and variance groups, and can be used with permutations, sign flippings, or both combined. We evaluate the method for various dependence structures, apply it to real data from the Human Connectome Project (HCP) as an example application, show that false positives can be avoided in such cases, and provide a software implementation of the proposed approach.
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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.