Nonlinear Models for Repeated Measurement Data
Author:   Marie Davidian ,  David .M Giltinan ,  David .M. Giltinan (Genentech, Inc., South San Francisco, California, USA) ,  N. Reid (University of Toronto, Ontario, Canada)
Publisher:   Taylor & Francis Ltd
Volume:   62
ISBN:  

9780412983412


Pages:   376
Publication Date:   01 June 1995
Format:   Hardback
Availability:   In Print   Availability explained
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Nonlinear Models for Repeated Measurement Data


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Author:   Marie Davidian ,  David .M Giltinan ,  David .M. Giltinan (Genentech, Inc., South San Francisco, California, USA) ,  N. Reid (University of Toronto, Ontario, Canada)
Publisher:   Taylor & Francis Ltd
Imprint:   Chapman & Hall/CRC
Volume:   62
Dimensions:   Width: 15.20cm , Height: 2.20cm , Length: 22.90cm
Weight:   0.830kg
ISBN:  

9780412983412


ISBN 10:   0412983419
Pages:   376
Publication Date:   01 June 1995
Audience:   College/higher education ,  Professional and scholarly ,  Undergraduate ,  Postgraduate, Research & Scholarly
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

Table of Contents

Introduction. Nonlinear regression models for individual data. Hierarchical linear models. Hierarchical nonlinear models. Inference based on individual estimates. Inference based on linearization. Nonperametric and semiparametric inference. Bayesian inference. Pharamcokinetic and pharamacodynamic analysis. Analysis of assay data. Further applications. Open problems and discussion. References. Indices.

Reviews

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


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Davidian, Marie

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