Nonlinear Models in Medical Statistics

Front Cover
Oxford University Press, 2001 - Mathematics - 280 pages
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.
 

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Contents

Basic concepts
1
Practical aspects
23
Families of nonlinear regression functions
37
Epidemiology
49
Change points
57
Clinical trials
73
Quality of life
85
Pharmacokinetics
105
Pharmacodynamics
141
Assays and formulations
157
Molecular genetics
179
A Data and model examples from R
193
B Stochastic dependence structures
205
Markov processes
219
Bibliography
255
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About the author (2001)

J.K. Lindsey is a Professor of Biostatistics, Limburgs University, Belgium; Professor of Quantitative Methodology, University of Liege, Belgium.

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