Power calculation for group fMRI studies accounting for arbitrary design and temporal autocorrelation.
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.
Mumford
Jeanette A
JA
University of California Los Angeles, UCLA Department of Psychology, Box 951563, 1285 Franz Hall, Los Angeles, CA 90095, USA. mumford@ucla.edu
Nichols
Thomas E
TE
D000328:Adult; D000465:Algorithms; D001931:Brain Mapping / Q000379:methods*; D003198:Computer Simulation; D005072:Evoked Potentials, Auditory / Q000502:physiology*; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008959:Models, Neurological; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013067:Speech Perception / Q000502:physiology*; D013223:Statistics as Topic