Abstract
The rationale for employing a nonlinear iterative least-squares technique for fitting the well-known power function to oxygen consumption–body weight data is set forth. Twenty-six sets of routine or standard metabolism data from six authors were used to demonstrate the relative merits of two methods of calculating parameter values for the power function. The conclusion was reached that if accuracy in predicting oxygen consumption over a wide range of values of body weight is desired, an iterative curve fitting method may be superior to the much used technique of performing a linear regression on logarithmically transformed data.