Some bootstrap methods in nonlinear mixed-effect models

Nonlinear mixed-effect (NLME) models arise in many applied fields including pharmacokinetics. Several bootstrap methods are considered for estimating standard errors of parameter (both fixed and random effects) estimates in these models. Keeping in mind the issues that make the NLME different from the simple linear model, modifications of the classical bootstrap methods are suggested. Although the current work specifically relates to the models proposed by Lindstrom and Bayes (1990), and Vonesh and Carter (1992), the described methods should work as well in most other NLME models. Limited data analysis has been performed implementing some of the proposed bootstrap methodologies.