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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This book is a great introduction to the topic of nonlinear models and is probably the only book that deals with some of the concepts. Lindsey's writing style makes easy reading and very useful reference ... this book is a must for those working in early phase clinical trials, particularly in the discipline of pharmacokinetics and pharmacodynamics. (Pharmaceutical Statistics)
The book would benefit primarily those statisticians working in exploratory fields, particularly early drug development. It would also benefit those working in pharmacokinetics and pharmacodynamics. (Pharmaceutical Statistics)
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Hardcover. Condition: Near Fine. 1st. 280 pp including index, with charts graphs and illustrations throughout, 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. Seller Inventory # 45912
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