The DOI matches its Crossref record; 22 of the 22 references it cites were found in a registry or an index.
Power calculation for group fMRI studies accounting for arbitrary design and temporal autocorrelation
Open accessAbstract
When planning most scientific studies, one of the first steps is to carry out a power analysis to define a design and sample size that will result in a well-powered study. There are limited resources for calculating power for group fMRI studies due to the complexity of the model. Previous approaches for group fMRI power calculation simplify the study design and/or the variance structure in order to make the calculation possible. These approaches limit the designs that can be studied and may result in inaccurate power calculations. We introduce a flexible power calculation model that makes fewer simplifying assumptions, leading to a more accurate power analysis that can be used on a wide variety of study designs. Our power calculation model can be used to obtain region of interest (ROI) summaries of the mean parameters and variance parameters, which can be use to increase understanding of the data as well as calculate power for a future study. Our example illustrates that minimizing cost to achieve 80% power is not as simple as finding the smallest sample size capable of achieving 80% power, since smaller sample sizes require each subject to be scanned longer.
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“From this 20 participants per group (adolescent/adults) was recommended.”
From Multimodal evidence for delayed threat extinction learning in adolescence and young adulthood (2019) · cites this paper as [56]
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“The sample size was determined using sample estimates for group fMRI based on 80% power56.”
From Multimodal evidence for delayed threat extinction learning in adolescence and young adulthood (2019) · cites this paper as [56]
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Temporal Autocorrelation in Univariate Linear Modeling of FMRI Data
Woolrich, M. W., Ripley, B. D., Brady, M., & Smith, S. M. (2001) · NeuroImage · doi:10.1006/nimg.2001.0931 · Cited by 2,859
General multilevel linear modeling for group analysis in FMRI
Beckmann, C. F., Jenkinson, M., & Smith, S. M. (2003) · NeuroImage · doi:10.1016/s1053-8119(03)00435-x · Cited by 1,464
Estimating sample size in functional MRI (fMRI) neuroimaging studies: Statistical power analyses
Desmond, J. E., & Glover, G. H. (2002) · Journal of Neuroscience Methods · doi:10.1016/s0165-0270(02)00121-8 · Cited by 716
Classical and Bayesian Inference in Neuroimaging: Applications
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Empirical Analyses of BOLD fMRI Statistics
Zarahn, E., Aguirre, G. K., & D’Esposito, M. (1997) · NeuroImage · doi:10.1006/nimg.1997.0263 · Cited by 695
Stochastic Designs in Event-Related fMRI
Friston, K. J., Zarahn, E., Josephs, O., Henson, R. N., & Dale, A. M. (1999) · NeuroImage · doi:10.1006/nimg.1999.0498 · Cited by 634
Classical and Bayesian Inference in Neuroimaging: Theory
Friston, K. J., Penny, W. D., Phillips, C. L. M., Kiebel, S. J., Hinton, G. E., & Ashburner, J. (2002) · NeuroImage · doi:10.1006/nimg.2002.1090 · Cited by 597
Empirical Analyses of BOLD fMRI Statistics
Aguirre, G. K., Zarahn, E., & D’Esposito, M. (1997) · NeuroImage · doi:10.1006/nimg.1997.0264 · Cited by 474
Optimization of experimental design in fMRI: a general framework using a genetic algorithm
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Self-citationEvent-related functional magnetic resonance imaging: modelling, inference and optimization
Josephs, O., & Henson, R. N. A. (1999) · Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences · doi:10.1098/rstb.1999.0475 · Cited by 425
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Metadata
- Authors
- Mumford, J. A., & Nichols, T. E.
- Affiliations
- University of California, Los Angeles (US)
- Hammersmith Hospital (GB)
- Corresponding author
- Mumford, Jeanette A.
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2008-01
- Volume
- 39
- Issue
- 1
- Pages
- 261-268
- ISSN
- 1053-8119 (ISSN-L)
- PMC
- PMC2423281
- OpenAlex
- W1967252112
- Cited by
- 252
- References
- 22
- Citations by year
- 2026: 10 · 2025: 22 · 2024: 8 · 2023: 12 · 2022: 18 · 2021: 17 · 2020: 29 · 2019: 21 · 2018: 20 · 2017: 19 · 2016: 11 · 2015: 10 · 2014: 7 · 2013: 17 · 2012: 10
- FWCI
- 1.79
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health (R01 DA15410, R01 EB004346-01A1)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Keywords
- statistical power analysis, sample size determination, temporal autocorrelation, research design, neuroimaging
- MeSH terms
- Adult, Algorithms, Brain Mapping, Computer Simulation, Evoked Potentials, Auditory, Female, Humans, Image Enhancement, Image Interpretation, Computer-Assisted, Magnetic Resonance Imaging, Male, Models, Neurological, Sensitivity and Specificity, Speech Perception, Statistics as Topic, Reproducibility of Results
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