Abt K
Department of Biomathematics, Medical School, University of Frankfurt, Federal Republic of Germany.
J Clin Neurophysiol. 1990 Oct;7(4):519-34. doi: 10.1097/00004691-199010000-00007.
The multitude of electrodes and the large number of EEG variables used in neurophysiologic topography call for new inferential statistical concepts in the analysis of data from corresponding studies. These concepts must take into consideration that significance levels and confidence coefficients lose their numerical meaning in situations with many significance tests and/or interval estimates performed on the data from one sample of subjects or patients. The application of one of these concepts. Descriptive Data Analysis (DDA), is discussed, using the data from a real EEG mapping example. Also, the use of DDA is proposed for the judgement of normality of EEG maps.
神经生理地形图中使用的大量电极和众多脑电图变量,要求在分析相应研究的数据时采用新的推断统计概念。这些概念必须考虑到,在对来自一组受试者或患者的数据进行多次显著性检验和/或区间估计的情况下,显著性水平和置信系数会失去其数值意义。本文讨论了其中一种概念——描述性数据分析(DDA)的应用,并使用了一个真实脑电图映射示例中的数据。此外,还建议使用DDA来判断脑电图图谱的正态性。