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Medical Applications of Finite Mixture Models (Statistics for Biology and Health) by Peter Schlattmann

Download Medical Applications of Finite Mixture Models (Statistics for Biology and Health)

Medical Applications of Finite Mixture Models (Statistics for Biology and Health) Peter Schlattmann
Language: English
Page: 246
Format: pdf
ISBN: 3540686509, 9783540686507
Publisher: Springer

Review

From the reviews: “This book is intended as a resource for working statisticians, epidemiologists, pharmacokineticists and physicians. … the material is most suitable for working (bio)statisticians who wish to apply finite mixture models. The book would make a good supplementary textbook for say a second year master’s level course. … there are many nice examples demonstrating finite mixture modeling. … Each example is extremely well motivated. … Overall, the book is well written … .” (Timothy D. Johnson, Journal of the American Statistical Association, Vol. 106 (493), March, 2011) “This lucid and consistent presentation should be welcome by researchers in the greater domain of biomedical research. This impressive monograph attempts to cover the use of finite mixture models in a variety of biomedical problems, illustrated by appropriate case studies. … Statistical analysis has been presented consistently at an intermediate level so that researchers in a broader biomedical field, constituting the general audience of this book, can appreciate the rationality of statistical modelling and analysis to a greater extent.” (Pranab K. Sen, International Statistical Review, Vol. 79 (2), 2011)

From the Back Cover

The book shows how to model heterogeneity in medical research with covariate adjusted finite mixture models. The areas of application include epidemiology, gene expression data, disease mapping, meta-analysis, neurophysiology and pharmacology. After an informal introduction the book provides and summarizes the mathematical background necessary to understand the algorithms. The emphasis of the book is on a variety of medical applications such as gene expression data, meta-analysis and population pharmacokinetics. These applications are discussed in detail using real data from the medical literature. The book offers an R package which enables the reader to use the methods for his/her needs.