Schneiderman E D, Willis S M, Kowalski C J, Guo I Y
Department of Oral and Maxillofacial Surgery, Baylor College of Dentistry, Dallas, TX 75266-0677.
Int J Biomed Comput. 1994 May;35(4):247-54.
A PC program, written in GAUSS386i, implementing Zerbe's (Growth, 43 (1979) 263-272) procedure for diagnosis on the basis of longitudinal data is described, illustrated and made available to interested readers. Given longitudinal observations on N normal individuals, this technique can be used to characterize normal growth, velocity and acceleration, and to determine whether or not a new individual can be considered normal with respect to any or all of these parameters. Missing data are allowed, and there is no requirement that the variable whose growth is being monitored has a normal distribution. The method and program are illustrated using a data set with a substantial amount of missing data. Information on obtaining a copy of the program and hardware requirements are given in the Appendix.