Maiwald M, Bannert M, Rogge K E
Z Klin Psychol Psychopathol Psychother. 1991;39(3):240-53.
A data set of physiological (blood pressure, body weight, pulse rate) as well as psychological (adjective list by Sokolow et al.) variables collected by a patient in 1985 is analysed. Initially, by identifying time series models, subsequently, by estimating parameters and, eventually, by cross correlating all variables pair wise. With regard to different time intervals (the whole year, 2-months-intervals) several ARIMA-models apply for a description of the psychophysiological variables. Results obtained by time series analyses are confirmed by spectral analyses. For distinct time sections (i.e. Sep.--Oct., Nov.--Dec.) cross correlations reveal a seven day periodicity which corresponds to a psychophysiological pattern. Time series analyses of single case data are considered as a valuable research strategy which in some cases allows the detection of the underlying processes.
分析了一位患者在1985年收集的生理变量（血压、体重、脉搏率）以及心理变量（索科洛夫等人的形容词列表）的数据集。首先，通过识别时间序列模型，随后，通过估计参数，最终，通过对所有变量进行两两交叉相关分析。对于不同的时间间隔（一整年、两个月的间隔），几个自回归积分移动平均（ARIMA）模型适用于描述心理生理变量。时间序列分析得到的结果通过频谱分析得到证实。对于不同的时间段（即9月至10月、11月至12月），交叉相关分析揭示了一种与心理生理模式相对应的七天周期性。单病例数据的时间序列分析被认为是一种有价值的研究策略，在某些情况下可以检测到潜在的过程。
