A NOTE ON FITTING ONE-COMPARTMENT MODELS - NONLINEAR LEAST-SQUARES VERSUS LINEAR LEAST-SQUARES USING TRANSFORMED DATA

Drug concentrations in one‐compartment systems are frequently modeled using a single exponential function. Two methods of estimation are commonly used for determining the parameters of such a model. In the first method, non‐linear least‐squares regression is used to calculate the parameters. In the second method, the data are first transformed by a logarithmic function, and then the log‐concentration data are fit using linear least‐squares regression. The assumptions for fitting these models are discussed with special emphasis on which data points are most influential in determining parameter values. The similarities between fitting a linear regression model to the log‐concentration data and fitting a weighted regression model to the original data are noted. An example is presented that illustrates the differences in fitting a model to the log‐transformed data versus fitting unweighted and weighted models to the original‐scale data. Copyright © 1990 John Wiley & Sons, Ltd.