Woods R P
Division of Brain Mapping, UCLA School of Medicine 90095, USA.
Neuroimage. 1996 Dec;4(3 Pt 3):S84-94. doi: 10.1006/nimg.1996.0058.
Intergroup comparisons pose unique challenges in the analysis of functional imaging data. Imperfections in intersubject stereotaxis can give rise to artifactual results and make it particularly important to allow for intersubject differences in task-related changes when formulating statistical models. Because intergroup comparisons generally involve inferences about the populations from which the subjects were drawn rather than inferences about the particular subjects themselves, subjects must be treated as random rather than fixed effects in the statistical model. These requirements, when combined with the need to adjust for multiple spatial comparisons, result in low statistical power when the number of subjects in each group is small. Functional imaging studies to identify differences between groups generally require many more subjects than other types of functional imaging studies and require careful advance planning to maximize the likelihood of reaching meaningful conclusions.
在功能成像数据分析中，组间比较带来了独特的挑战。受试者间立体定位的不精确可能导致人为结果，并且在制定统计模型时考虑任务相关变化中的受试者间差异就显得尤为重要。由于组间比较通常涉及对抽取受试者的总体进行推断，而非对特定受试者本身进行推断，因此在统计模型中必须将受试者视为随机效应而非固定效应。这些要求，再加上需要对多个空间比较进行校正，当每组中的受试者数量较少时，会导致统计功效较低。识别组间差异的功能成像研究通常比其他类型的功能成像研究需要更多的受试者，并且需要仔细的预先规划，以最大程度地提高得出有意义结论的可能性。
