Includes bibliographical references (pages 259-293) and index
Mixture of Normal Distributions for Continuous Data -- Mixture of Gamma Distributions for Continuous Non-Normal Data -- Mixture of Generalized Linear Models for Count or Categorical Data -- Mixture Models for Survival Data -- Advanced Mixture Modelling with Random-Effects Components -- Advanced Mixture Models for Multilevel or Repeated-Measured Data -- Advance Mixture Models for Correlated Multivariate Continuous Data -- Miscellaneous: Handling of Missing Data -- Miscellaneous: Cluster Analysis of "Big Data" Using Mixture Models
"Mixture Modelling for Medical and Health Sciences provides a direct connection between theoretical developments in mixture modelling and their applications in real world problems. The book describes the development of the most important concepts through comprehensive analyses of real and practical examples taken from real-life research problems in medical and health sciences. This approach represents balance between "theory" and "practice", stimulating readers and enhancing their capacity to apply mixture models in data analysis. Full of reproducible examples using software code and publicly-available data, the book is suitable for graduate-level students, researchers, and practitioners who have a basic grounding in statistics and would like to explore the use of mixture models to analyse their experiments and research data."-- Publisher's description
