Bhaumik Dulal K, Roy Anindya, Lazar Nicole A, Kapur Kush, Aryal Subhash, Sweeney John A, Patterson Dave, Gibbons Robert D
Center for Health Statistics, University of Illinois at Chicago, 1601 W Taylor Street (MC 912), Chicago, IL 60612, United States.
Stat Methodol. 2009 Mar;6(2):133-146. doi: 10.1016/j.stamet.2008.05.003.
Modern methods for imaging the human brain, such as functional magnetic resonance imaging (fMRI) present a range of challenging statistical problems. In this paper, we first develop a large sample based test for between group comparisons and use it to determine the necessary sample size in order to obtain a target power via simulation under various alternatives for a given pre-specified significance level. Both testing and sample size calculations are particularly critical for neuroscientists who use these new techniques, since each subject is expensive to image.
现代人类大脑成像方法，如功能磁共振成像（fMRI），提出了一系列具有挑战性的统计问题。在本文中，我们首先开发了一种基于大样本的组间比较检验方法，并通过模拟在给定的预先指定的显著性水平下的各种备择假设，使用该方法来确定必要的样本量，以获得目标检验功效。检验和样本量计算对于使用这些新技术的神经科学家来说尤为关键，因为对每个受试者进行成像的成本都很高。
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