A common objective in longitudinal studies is to characterize the relationship between a
longitudinal response process and a time-to-event. Considerable recent interest has …

Nonlinear mixed effects models for data in the form of continuous, repeated measurements
on each of a number of individuals, also known as hierarchical nonlinear models, are a …

The first edition of Analysis for Longitudinal Data has become a classic. Describing the
statistical models and methods for the analysis of longitudinal data, it covers both the …

Semiparametric regression is concerned with the flexible incorporation of non-linear
functional relationships in regression analyses. Any application area that benefits from …

It's been over a decade since the first edition of Measurement Error in Nonlinear Models
splashed onto the scene, and research in the field has certainly not cooled in the interim. In …

Over the last 20 years, comprehensive strategies for treating measurement error in complex
models and accounting for the use of extra data to estimate measurement error parameters …

Nonlinear measurement data arise in a wide variety of biological and biomedical
applications, such as longitudinal clinical trials, studies of drug kinetics and growth, and the …

With contributions from some of the most prominent researchers in the field, this carefully
edited collection provides a clear, comprehensive, and unified overview of recent …

The focus of this book is primarily on the development of pharmacokinetic and
pharmacokinetic-pharmacodynamic models. Models that are reported in the literature are …

Integrates the latest theory, methodology and applications related to the design and analysis
of repeated measurement. The text covers a broad range of topics, including the analysis of …