A comparison of methods of fitting several models to nutritional response data.
A variety of models have been proposed to fit nutritional input-output response data. The models are typically nonlinear; therefore, fitting the models usually requires sophisticated statistical software and training to use it. An alternative tool for fitting nutritional response models was developed by using widely available and easier-to-use Microsoft Excel software. The tool, implemented as an Excel workbook (NRM.xls), allows simultaneous fitting and side-by-side comparisons of several popular models. This study compared the results produced by the tool we developed and PROC NLIN of SAS. The models compared were the broken line (ascending linear and quadratic segments), saturation kinetics, 4-parameter logistics, sigmoidal, and exponential models. The NRM.xls workbook provided results nearly identical to those of PROC NLIN. Furthermore, the workbook successfully fit several models that failed to converge in PROC NLIN. Two data sets were used as examples to compare fits by the different models. The results suggest that no particular nonlinear model is necessarily best for all nutritional response data.
Vedenov
D
D
Department of Agricultural and Applied Economics, The University of Georgia, Athens, GA 30602-2772, USA.
Pesti
G M
GM
D000465:Algorithms; D000821:Animal Feed; D000824:Animal Nutritional Physiological Phenomena / Q000502:physiology*; D000818:Animals; D003201:Computers; D008433:Mathematics; D008954:Models, Biological; D015233:Models, Statistical; D009751:Nutritional Requirements; D012984:Software