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... Ausführliche Beschreibung

1. Person: Schlattmann, Peter
Weitere Körperschaften: SpringerLink (Online service)
Weitere Personen: SpringerLink (Online service)
Format: E-Buch
Sprache: English
Veröffentlicht: Berlin, Heidelberg Springer Berlin Heidelberg 2009, 2009
Beschreibung: X, 246 p. 74 illus online resource
Ausgabe: 1st ed. 2009
Serien: Statistics for Biology and Health
Schlagworte: Mathematical statistics
Epidemiology
Statistics for Life Sciences, Medicine, Health Sciences
Statistical methods
Biostatistics
Epidemiology
Public Health
Statistics
Statistics and Computing/Statistics Programs
Online Zugang: Volltext
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245 0 0 |a Medical Applications of Finite Mixture Models  |h Elektronische Ressource  |c by Peter Schlattmann 
250 |a 1st ed. 2009 
260 |a Berlin, Heidelberg  |b Springer Berlin Heidelberg  |c 2009, 2009 
300 |a X, 246 p. 74 illus  |b online resource 
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 
653 |a Mathematical statistics 
653 |a Epidemiology 
653 |a Statistics for Life Sciences, Medicine, Health Sciences 
653 |a Statistical methods 
653 |a Biostatistics 
653 |a Epidemiology 
653 |a Public Health 
653 |a Statistics 
653 |a Statistics and Computing/Statistics Programs 
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989 |b Springer  |a Springer eBooks 2005- 
490 0 |a Statistics for Biology and Health 
856 |u https://doi.org/10.1007/978-3-540-68651-4?nosfx=y  |x Verlag  |3 Volltext 
082 0 |a 519.5 
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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