Nonlinear Models for Repeated Measurement Data
Editorial Reviews
Review
…gives a very well-written account of the field over the past few decades, focusing 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 computational methods for maximum likelihood estimation. There is a leaning 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
Book Description
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 model and its extensions.
Nonlinear Models for Repeated Measurement Data
Nonlinear Models for Repeated Measurement Data,Marie Davidian,David .M. Giltinan,Chapman & Hall/CRC,0412983419,Biostatistics,Experimental design,Mathematical Statistics,Mathematics,Multivariate analysis,Probability & Statistics - General,Science,Science/Mathematics,Weights & Measures,Mathematical modelling,Mathematics / Statistics,Mathematics for scientists & engineers,Probability & statistics
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