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 themathematical 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. Covers wide range of applications of finite mixture models in the health sciencesAuthor provides related R package INDICE: Introduction - 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.
- ISBN: 978-3-540-68650-7
- Editorial: Springer
- Encuadernacion: Cartoné
- Páginas: 200
- Fecha Publicación: 01/10/2008
- Nº Volúmenes: 1
- Idioma: Inglés