Synopses & Reviews
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 of statistical modelling and of generalized linear models. It begins with a general introduction to nonlinear models, comparing them to generalized linear models, descriptions of data handling and formula definition and a summary of 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 moleuclar genetics.
Table of Contents
Preface 1. Basic Concepts
2. Practical Aspects
3. Families of nonlinear regression functions
4. Epidemiology
5. Clinical trials
6. Quality of Life
7. Pharmacokinetics
8. Pharmacodynamics
9. Assays and formulations
10. Molecular Genetics
Appendix A Data and Model examples from R
Appendix B Stochastic dependence structures
Appendix C Data tablesfor the exercises
Bibliography
Author Index
Subject Index