Longer-term growth prediction using GAUSS.
In several areas of biomedicine, one needs to predict future measurements for a growing individual on the basis of longitudinal data. Here we consider the problem of estimating the values of a given measurement for a particular individual at T-T* points in time, given T* observations on that individual, and all T values for a sample of N "similar" individuals. This extends our previous discussion [Schneiderman et al., Comput. Biol. Med. 22, 181-188 (1992)], which was limited to the case T* = T-1, to longer-term predictions. We again make a user-friendly GAUSS program available to perform the associated computations. Examples illustrating the use of the program and the accuracy of the predictions it provides are included.
Department of Oral and Maxillofacial Surgery, Baylor College of Dentistry, Dallas, TX 75246.
E D
ED
Schneiderman
S M
SM
Willis
C J
CJ
Kowalski
T R
TR
Ten Have
D000465:Algorithms; D000818:Animals; D005544:Forecasting; D006128:Growth; D008253:Macaca mulatta; D008297:Male; D008334:Mandible / Q000254:growth & development; D008954:Models, Biological; D012984:Software; D013997:Time Factors