Cited by 252Functional Brain Connectivity StudiesAdvanced MRI Techniques and ApplicationsStatistical Methods in Clinical Trials

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Power calculation for group fMRI studies accounting for arbitrary design and temporal autocorrelation

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Mumford, Jeanette A., Nichols, Thomas E.·2008·NeuroImage

DOI 10.1016/j.neuroimage.2007.07.061PMC PMC2423281

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Abstract

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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Authors: Mumford, J. A., & Nichols, T. E.
Affiliations: University of California, Los Angeles (US)
Hammersmith Hospital (GB)
Corresponding author: Mumford, Jeanette A.
ORCID: Mumford, Jeanette A.
Nichols, Thomas E.
Venue: NeuroImage
Publisher: Elsevier BV
Published: 2008-01
Volume: 39
Issue: 1
Pages: 261-268
ISSN: 1053-8119 (ISSN-L)
DOI: 10.1016/j.neuroimage.2007.07.061
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: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
www.elsevier.com/legal/tdmrep-license (tdm)
doi.org/10.15223/policy-017 (stm-asf)
doi.org/10.15223/policy-037 (stm-asf)
doi.org/10.15223/policy-012 (stm-asf)
doi.org/10.15223/policy-029 (stm-asf)
doi.org/10.15223/policy-004 (stm-asf)
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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Power calculation for group fMRI studies accounting for arbitrary design and temporal autocorrelation

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