Medical Applications of Finite Mixture Models

  • Peter Schlattmann

Part of the Statistics for Biology and Health book series (SBH)

Table of contents

  1. Front Matter
    Pages 1-10
  2. Peter Schlattmann
    Pages 1-6
  3. Peter Schlattmann
    Pages 1-22
  4. Peter Schlattmann
    Pages 1-26
  5. Peter Schlattmann
    Pages 1-51
  6. Peter Schlattmann
    Pages 1-36
  7. Peter Schlattmann
    Pages 1-10
  8. Peter Schlattmann
    Pages 1-17
  9. Back Matter
    Pages 1-26

About this book

Introduction

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.

Keywords

Computing Health Sciences Mixture Models Statistics epidemiology

Authors and affiliations

  • Peter Schlattmann

There are no affiliations available

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-540-68651-4
  • Copyright Information Springer-Verlag Berlin Heidelberg 2009
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-3-540-68650-7
  • Online ISBN 978-3-540-68651-4
  • Series Print ISSN 1431-8776
  • About this book