ArticleeLife2021
Bayesian inference of population prevalence.
Article in eLife, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.
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.
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
38 citing papers in PubMed.
- Self-supervised learning yields representational signatures of category-selective cortex.Communications biology · 2026Article
- Effects of social exclusion on following the gaze of others.British journal of psychology (London, England : 1953) · 2026Article
- Increasing power for detecting awareness: a new approach to test group level objective performance.Neuroscience of consciousness · 2026Article
- Data-driven psychophysical methods to diversify SIAs and address bias.Journal on multimodal user interfaces · 2026Article
- Individual differences do not mask effects of unconscious processing.Psychonomic bulletin & review · 2025Review
- In silico discovery of representational relationships across visual cortex.Nature human behaviour · 2025Article
- Intentional binding effect depends on conscious access to the sensory consequences of action.Communications psychology · 2025Article
- Individual differences shape conceptual representation in the brain.bioRxiv : the preprint server for biology · 2025Article
- The brain computes dynamic facial movements for emotion categorization using a third pathway.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Wearable MEG data recorded during human stepping.Data in brief · 2025Article
- Overlapping Cortical Substrate of Biomechanical Control and Subjective Agency.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
- Decoding the Spatiotemporal Dynamics of Neural Response Similarity in Auditory Processing: A Multivariate Analysis Based on OPM-MEG.Human brain mapping · 2025Article
- Effect of a Plant-Based Nootropic Supplement on Perceptual Decision-Making and Brain Network Interdependencies: A Randomised, Double-Blinded, and Placebo-Controlled Study.Brain sciences · 2025Article
- Bayesian p-curve mixture models as a tool to dissociate effect size and effect prevalence.Communications psychology · 2025Article
- Using cluster-based permutation tests to estimate MEG/EEG onsets: How bad is it?The European journal of neuroscience · 2025Article
- Cross-modal congruency modulates evidence accumulation, not decision thresholds.Frontiers in neuroscience · 2025Article
- The Concise Language Paradigm (CLaP), a framework for studying the intersection of comprehension and production: electrophysiological properties.Brain structure & function · 2024Article
- Concurrent perception of competing predictions: A "split-stimulus effect".Journal of vision · 2024Article
- Literacy in nonspeaking autistic people.Autism : the international journal of research and practice · 2024Article
- Specified functions of the first two fixations in face recognition: Sampling the general-to-specific facial information.iScience · 2024Article
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
Within neuroscience, psychology, and neuroimaging, the most frequently used statistical approach is null hypothesis significance testing (NHST) of the population mean. An alternative approach is to perform NHST within individual participants and then infer, from the proportion of participants showing an effect, the prevalence of that effect in the population. We propose a novel Bayesian method to estimate such population prevalence that offers several advantages over population mean NHST. This method provides a population-level inference that is currently missing from study designs with small participant numbers, such as in traditional psychophysics and in precision imaging. Bayesian prevalence delivers a quantitative population estimate with associated uncertainty instead of reducing an experiment to a binary inference. Bayesian prevalence is widely applicable to a broad range of studies in neuroscience, psychology, and neuroimaging. Its emphasis on detecting effects within individual participants can also help address replicability issues in these fields.
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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.