The effect of a feature of regression disturbance on the efficiency of fitting growth curves

Growth curve parameters are usually estimated by employing non-linear regression. In the present study this method was found to be inefficient for fitting growth curves, since the magnitude of random deviations of body weight greatly increases with age (heteroskedastic regression disturbance). Simulated samples of broiler body weights at different ages were generated and the associated Gompertz growth curve parameters were estimated employing three methods. Comparison of the efficiency of these methods in fitting Gompertz growth curve under this regression disturbance were performed. The results indicate that the most efficient method to estimate growth curve parameters is "weighted non-linear regression". The efficiency of this method was found to be much higher than that of conventional non-linear regression. These findings should be taken into consideration when fitting growth curves, in general, as well as for the Gompertz equation.