Nonlinear Models for Repeated Measurement Data: Vol 62

"gives a very well-written account of the field over the past few decades, focussing mainly on US work and including much of the author's own, plus a glimpse of the future. It fairly reflects that literature over the years in dwelling at length on certain compuational methods for maximum likelihood estimation. There is aleaning toward biopharmaceutical applications, this being a field in which the authors are acknowledged authorities. There are no exercises, but enough detail of the methodology is given, together with helpful guidance on available software, to enable the keen novice to try his hand. Lastly, I hope I'll be forgiven for just adding a couple of citations to those given in the book: a slightly different perspective on nonlinear regression models for repeated measures is described briefly in Crowder and Hand (1990, Section 9.4) and at greater length in Hand and Crowder (1995, chapter 8). --M. J. Crowder, Biometrics, September 1997