title: Trees and tracking.
abstract: Epidemiologists have used the term 'tracking' to connote an individual's maintenance of relative rank of some longitudinally measured characteristic over a given time span. To assess the extent to which an attribute tracks we have first to summarize individual growth curves, and second to quantify the notion of maintenance of relative rank, both in the face of random error. A sequence of papers appearing in 1981 provided differing methodologies for appraising tracking. Here we take a different approach to tracking by using regression trees for longitudinal data. The above two concerns are simultaneously addressed in that the procedure identifies subgroups, defined in terms of covariates, within which the collection of growth curves is homogeneous. After reviewing the existing approaches to tracking we describe the tree-structured methodology, and present an illustrative example pertaining to lung function growth in children.
authors.affiliation: Division of Biostatistics, University of California, San Francisco 94143-0560.
authors.forename: M R
authors.initials: MR
authors.lastname: Segal
authors.forename: I B
authors.initials: IB
authors.lastname: Tager
mesh_terms: D015982:Bias; D002648:Child; D002675:Child, Preschool; D002908:Chronic Disease / Q000145:classification / Q000453:epidemiology*; D003663:Decision Trees; D005260:Female; D005541:Forced Expiratory Volume; D006801:Humans; D008137:Longitudinal Studies; D008173:Lung Diseases, Obstructive / Q000175:diagnosis / Q000453:epidemiology / Q000503:physiopathology; D008297:Male; D011159:Population Surveillance / Q000379:methods*; D012044:Regression Analysis; D012307:Risk Factors