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Computation of Foulkes and Davis' nonparametric tracking index using GAUSS
Author(s) -
Schneiderman Emet D.,
Kowalski Charles J.,
Ten Have Thomas R.,
Willis Stephen M.
Publication year - 1992
Publication title -
american journal of human biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.559
H-Index - 81
eISSN - 1520-6300
pISSN - 1042-0533
DOI - 10.1002/ajhb.1310040318
Subject(s) - statistic , nonparametric statistics , computation , gauss , statistics , tracking (education) , rank (graph theory) , parametric statistics , population , mathematics , set (abstract data type) , confidence interval , cohen's kappa , computer science , data mining , algorithm , medicine , combinatorics , psychology , pedagogy , physics , quantum mechanics , programming language , environmental health
Foulkes and Davis (1981) define tracking as the maintenance of relative rank over a given time span. This paper outlines the development of their statistic, based on a set of individual growth profiles, which estimates the degree of tracking observed in a one‐sample longitudinal data set and shows how confidence intervals for the corresponding population parameter may be constructed. An example using a measure of skeletal growth is given and a GAUSS program to do the computations is provided. (Information on obtaining the GAUSS program is provided in the Appendix.) Properties of this statistical approach to tracking are contrasted with another non‐parametric method based on Cohen's kappa statistic. © 1992 Wiley‐Liss, Inc.