Nonlinear Models for Medical Statistics by J.K. LindseyNonlinear Models for Medical Statistics by J.K. Lindsey

Nonlinear Models for Medical Statistics

byJ.K. Lindsey

Hardcover | September 20, 2001

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This text provides an introduction to the use of nonlinear models in medical statistics, It is a practical text rather than a theoretical one and assumes a basic knowledge in statistical modelling and of generalized linear models. The book first provides a general introduction to nonlinear models, comparing them to generalized linear models. It describes data handling and formula definition and summarises the principal types of nonlinear regression formulae. there is an emphasis on techniques for non-normal data.Following chapters provide detailed examples of applications in various areas of medicine, epidemiology, clinical trials, quality of life, pharmokinetics, pharmacodynamics, assays and formulations, and molecular genetics.The book concludes with appendicies describing data handling and model formulae in more detail, and given ways of modelling dependencies in repeated measurements, and data for the exercises.
J.K. Lindsey is a Professor of Biostatistics, Limburgs University, Belgium; Professor of Quantitative Methodology, University of Liege, Belgium.
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Title:Nonlinear Models for Medical StatisticsFormat:HardcoverDimensions:292 pages, 9.21 × 6.14 × 0 inPublished:September 20, 2001Publisher:Oxford University PressLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:0198508123

ISBN - 13:9780198508120

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Table of Contents

Preface1. Basic concepts2. Practical aspects3. Families of nonlinear regression functions4. Epidemiology5. Clinical trials6. Quality of life7. Pharmacokinetics8. Pharmacodynamics9. Assays and formulations10. Molecular geneticsAppendicesA. Data and model examples from RB. Stochastic dependence structuresC. Data tables for the exercisesBibliographyAuthor indexSubject index

Editorial Reviews

`Statisticians will find much to interest them in the book.'International Journal of Epidemiology