Longer-term growth prediction using GAUSS. Academic Article

abstract

• 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.

authors

• Schneiderman, Emet

published proceedings

• Comput Biol Med

author list (cited authors)

• Schneiderman, E. D., Willis, S. M., Kowalski, C. J., & Ten Have, T. R.

citation count

• 3

complete list of authors

• Schneiderman, ED||Willis, SM||Kowalski, CJ||Ten Have, TR

publication date

• January 1993

publisher

• Elsevier  Publisher

published in

• Computers in Biology and Medicine  Journal

keywords

• Algorithms
• Animals
• Forecasting
• Growth
• Macaca Mulatta
• Male
• Mandible
• Models, Biological
• Software
• Time Factors

Digital Object Identifier (DOI)

• 10.1016/0010-4825(93)90146-r

start page

• 149

end page

• 154

volume

• 23

issue

• 2

URL

• http://dx.doi.org/10.1016/0010-4825(93)90146-r