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.
Schneiderman
E D
ED
Department of Oral and Maxillofacial Surgery, Baylor College of Dentistry, Dallas, TX 75246.
Willis
S M
SM
Kowalski
C J
CJ
Ten Have
T R
TR
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