title: [Time series analysis of patient self-assessed psychophysiologic variables].
abstract: 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.
authors.forename: M
authors.initials: M
authors.lastname: Maiwald
authors.forename: M
authors.initials: M
authors.lastname: Bannert
authors.forename: K E
authors.initials: KE
authors.lastname: Rogge
mesh_terms: D000339:Affect; D001143:Arousal; D001794:Blood Pressure; D001835:Body Weight; D006339:Heart Rate; D006801:Humans; D006973:Hypertension / Q000523:psychology*; D015233:Models, Statistical; D011602:Psychophysiologic Disorders / Q000523:psychology*; D012621:Seasons
vernacular_title: Zeitreihenanalyse von patientenselbstgemessenen psychophysiologischen Variablen.