Medical Applications of Finite Mixture Models

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 sum...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριος συγγραφέας: Schlattmann, Peter (Συγγραφέας)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg, 2009.
Σειρά:Statistics for Biology and Health,
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
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245 1 0 |a Medical Applications of Finite Mixture Models  |h [electronic resource] /  |c by Peter Schlattmann. 
264 1 |a Berlin, Heidelberg :  |b Springer Berlin Heidelberg,  |c 2009. 
300 |a X, 246 p. 74 illus.  |b online resource. 
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505 0 |a 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. 
520 |a 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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