Multi-level nonlinear mixed effects (ML-NLME) models have received a great deal of attention in recent years because of the flexibility they offer in handling the repeated-measures data arising from various disciplines. In this study, we propose both maximum likelihood and restricted maximum...

Nonlinear mixed-effects (NLME) models are popular in many longitudinal studies, including those on human immunodeficiency virus (HIV) viral dynamics, pharmacokinetic analysis, and studies of growth and decay analysis. Generally, the normality of the random effects is a common assumption in NLME...

Nonlinear mixed-effects (NLME) models and generalized linear mixed models (GLMM) are popular in the analyses of longitudinal data and clustered data. Covariates are often introduced to partially explain the large between individual (cluster) variation. Many of these covariates, however, contain...

A virologic marker, the number of HIV RNA copies or viral load, is currently used to evaluate antiretroviral (ARV) therapies in AIDS clinical trials. This marker can be used to assess the antiviral potency of therapies, but may be easily affected by clinical factors such as drug exposures and...