Post-hoc power estimation for topological inference in fMRI
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Summary
It is shown how estimating the number of activated peaks or clusters enables one to estimate post-hoc how powerful the selection procedure performs, and raises awareness on how much activation is potentially missed.
- Type
- article
- Published
- 2014-01-01
- Cited by
- 36
- References
- 49
- Access
- Open access
- OpenAlex
- https://openalex.org/W1987580254
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:9767673
Keywords
Computer science, Thresholding, False positive paradox, Inference, Focus (optics)
References
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- MULTIPLE TESTING OF LOCAL MAXIMA FOR DETECTION OF PEAKS IN 1D
- Post-hoc power estimation in large-scale multiple testing problems
- A sensorimotor paradigm for Bayesian model selection
- A Reference Effect Approach for Power Analysis in fMRI
- Toward discovery science of human brain function
- Precursors of the, Journal of the Royal Statistical Society
- Improved Assessment of Significant Activation in Functional Magnetic Resonance Imaging (fMRI): Use of a Cluster‐Size Threshold
- Threshold-free cluster enhancement: Addressing problems of smoothing, threshold dependence and localisation in cluster inference
- The Geometry of Random Fields
- Information-based functional brain mapping.
- Meaningful design and contrast estimability in FMRI
- A Three-Dimensional Statistical Analysis for CBF Activation Studies in Human Brain
Cited by
- Data-analytical stability of cluster-wise and peak-wise inference in fMRI data analysis.
- Cluster failure: Why fMRI inferences for spatial extent have inflated false-positive rates
- The Neural Correlates of Emotion Regulation by Implementation Intentions
- Brain functional and structural changes in adult ADHD and their relation to long-term stimulant treatment
- Practical and accurate approaches to statistical significance and power for fMRI
- Fixed versus random effects models for fMRI meta-analysis.
- Power and sample size calculations for fMRI studies based on the prevalence of active peaks
- Best Practices in Data Analysis and Sharing in Neuroimaging using MRI
- Brain abnormalities in adults with Attention Deficit Hyperactivity Disorder revealed by voxel-based morphometry.
- Statistical power and prediction accuracy in multisite resting‐state fMRI connectivity
- Data analytical stability of measuring brain activation in fMRI studies
- Is Bonferroni correction more sensitive than Random Field Theory for most fMRI studies
- Statistical power and measurement bias in multisite resting-state fMRI connectivity
- Sample Size Determination for High Dimensional Neuroimaging Studies Controlling False Discovery Rate
- Neurodesign: Optimal Experimental Designs for Task fMRI
- How sample size influences the replicability of task-based fMRI
- The influence of study characteristics on coordinate-based fMRI meta-analyses
- Assessing robustness against potential publication bias in coordinate based fMRI meta-analyses using the Fail-Safe N
- The relation between statistical power and inference in fMRI
- The Influence of Study-Level Inference Models and Study Set Size on Coordinate-Based fMRI Meta-Analyses
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