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Library,Documentation and Information Science Division

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Medical Applications of Finite Mixture Models [electronic resource] / by Peter Schlattmann.

By: Schlattmann, Peter [author.].
Contributor(s): SpringerLink (Online service).
Material type: TextTextSeries: Statistics for Biology and Health: Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2009Description: X, 246 p. 74 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783540686514.Subject(s): Statistics | Statistical methods | Mathematical statistics | Epidemiology | Statistics for Life Sciences, Medicine, Health Sciences | Public Health | Biostatistics | Statistics and Computing/Statistics Programs | EpidemiologyAdditional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification: 519.5 Online resources: Click here to access online
Contents:
Overview over the Book -- - Heterogeneity in Medicine -- Modeling Count Data -- Theory and Algorithms -- Disease Mapping and Cluster Investigations -- Modeling Heterogeneity in Psychophysiology -- Investigating and Analyzing Heterogeneity in Meta-Analysis -- Analysis of Gene Expression Data.
In: Springer eBooksSummary: 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.
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Overview over the Book -- - Heterogeneity in Medicine -- Modeling Count Data -- Theory and Algorithms -- Disease Mapping and Cluster Investigations -- Modeling Heterogeneity in Psychophysiology -- Investigating and Analyzing Heterogeneity in Meta-Analysis -- Analysis of Gene Expression Data.

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.

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