title: Application of time series analysis in the clinical setting.
abstract: A growth curve time series model is characterized by a biological growth pattern with random deviations added to this basic pattern. Various types are reviewed including the homeostatic model which is a special and simple type characterized by zero growth. The limitations to the use of time series analysis in the clinical setting include lack of initial baseline values and difficulties in specifying in quantitative terms a relevant hypothesis alternative to the one postulated by the time series model. Some ongoing research addressing these problems is discussed.
authors.affiliation: Univerity Hospital (Rigshospitalet), Copenhagen, Denmark.
authors.forename: P
authors.initials: P
authors.lastname: Winkel
mesh_terms: D014408:Biomarkers, Tumor / Q000592:standards*; D019411:Clinical Laboratory Techniques / Q000592:standards*; D003627:Data Interpretation, Statistical; D003658:Decision Making, Computer-Assisted; D006801:Humans; D008954:Models, Biological; D015233:Models, Statistical; D013997:Time Factors
chemical_list: D014408:Biomarkers, Tumor