Extended quasi-likelihood is useful for analyzing intra-individual variability in pharmacokinetic regression models.

Abstract

The method of maximum extended quasi-likelihood (MEQL) can be viewed as an estimation method in the framework of generalized linear models. The method was applied to a pharmacokinetic problem in which the pharmacokinetic model was a nonlinear function of its parameters. The behavior of the method toward the estimation of a variance function was numerically compared with those of the generalized least squares (GLS) and extended least squares methods. In general, the MEQL and GLS methods were equally better. However, the MEQL estimator often showed smaller mean squared errors for the scaling parameter than the other two estimators. Such a generally comparable but partially distinct property of the MEQL method, as compared with the GLS method, is useful to pharmacokinetic analysis.