Nonlinear Models for Repeated Measurement Data

by Marie Davidian, David .M. Giltinan, D.R. Cox (Series Editor)

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 analysis of assay and laboratory data. Nonlinear Models for Repeated Measurement Data provides the first unified development of methods and models for data of this type, with a detailed treatment of inference for the nonlinear mixed effects and its extensions. A particular strength of the book is the inclusion of several detailed case studies from the areas of population pharmacokinetics and pharmacodynamics, immunoassay and bioassay development and the analysis of growth curves.

376 pages, Hardcover

First published June 1, 1995

Reviews

[David · Rating 5 out of 5]

What I learned from this book is that writing a book is a horrendous, but extraordinarily fulfilling, activity, to be undertaken only once in a lifetime.

And that, ten years after publication, you can still expect to get one or two e-mails a year, from places as far-flung as Uganda and Chile, wondering if maybe there is a typo on page 23. (Answer: yes, there is. Sorry.)

Sadly, during the year that it took to write the book, several friendships died on the vine, due to complete neglect on my part. On the other hand, I've had the experience of having people at professional meetings actually squeal in awe at learning my name and beg me to autograph their copy. And Marie (my co-author) and I remain close friends, a minor miracle. But, despite repeated requests from our publisher, neither of us has the stomach for a second edition.