Nonlinear Mixed Effects Model for Swine Growth

Purdue University 2002 Swine Research Report. Several nonlinear growth functions model weight as a function of days of age. Typically these functions are solved by iterative procedures that minimize the residual variance. The residual values (the observed minus predicted live weights) are assumed to be independent with a constant variance. Growth curves are often fit to serial live weight data typically every 14-21 days from 50 lbs. to 250 lbs. live weight. This serial data usually has underlying relationships or correlations amongst the serial live weight observations. Heavier pigs at birth and weaning usually have a competitive advantage and remain heavier than the remaining pigs of the group. Also, the variation amongst the pigs for live weight increases as age increases. This typical result contradicts the assumption that the residual values are independent and are a constant variance at each age. Also, marketing pigs in a specific live weight range or ending research trials at a specific live weight may bias the growth curves. To avoid discounts for pigs outside the specific pork processors optimal carcass weight ranges, the fastest growing pigs are marketed early and the slowest pigs are marketed later. By including live weight data after the fastest gaining pigs have been marketed, under predicts the true growth rates especially after 200 lbs. live weight (Schinckel and DeLange, 1996; Smith et al., 1999). The objective of this study was to evaluate the use of a mixed effects version of a commonly used live weight growth curve.