Mixture Modelling For Medical And Health Sciences Hardcover

New

Shu Kay Ng

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.

9781482236750

English

Apple Academic Press Inc.

21 May 2019

302

Dr Angus Ng is a Professor of Biostatistics in the School of Medicine, Griffith University. He was awarded his PhD degree in statistics from the University of Queensland in 1999. Dr Ng is an experienced researcher, with expertise in the fields of biostatistics, statistical modelling, cluster analysis, pattern recognition, machine learning, image analysis, and survival analysis. In these areas, he has more than 100 publications. The focus in the field of statistical modelling has been on the theory and applications of finite mixture models and on estimation via the EM algorithm. In his pioneering work on mixture model-based clustering of longitudinal data, he has elucidated a clear vision for the role of random-effects models to provide a sound theoretical framework for classifying correlated longitudinal data and exploring possible relationships among groups of correlated subjects. Dr Ng was awarded six ARC grants and has been actively involved in multidisciplinary research projects, NHMRC research projects, as well as consultancy and Government contracts. He is also a researcher with the Centre for Applied Health Economics (CAHE) and is an Associate Editor of the Journal of Statistical Computation and Simulation. Prof. Kelvin Yau is a retired professor in the department of management sciences at the City University of Hong Kong. His research interests include Generalized Linear Mixed Models, Multivariate Survival Analysis, Finite Mixture Models, Robust Estimation, Statistical Modelling and Zero-Inflated-Poisson Models. Liming Xiang is a professor of statistics at Nanyang Technological University in Singapore. She got her PhD degree in 2002 from the City University of Hong Kong. She serves as associate editor for Statistics in Medicine, Computational Statistics & Data Analysis and Journal of Statistical Computation and Simulation.

Liming Xiang

Kelvin Kai Wing Yau

"...The examples are rich in diagrams and tables, with explanatory text. The coding parts are less extensive. In any case, such a homogenic structure of the book definitely contributes to increased readability and understandability of quite complex topics. This is especially true in the later chapters, where more advanced methods are discussed...To conclude, this book is a definite asset for those interested in sample clustering and more specifically mixture modelling." - Gia Jgarkava, ISCB News, July 2020 "...(This book) by Shu Kay Ng, Liming Xiang and Kelvin Kai Wing Yau connects theoretical modelling to many real-world problems. Noteworthy features of this fascinating book include in-depth up-to-date knowledge on mixture modeling, random effects, among others...The bibliography is exhaustive and complete for the sake of the readers." - Ramalingam Shanmugam, JSCS, Aug 2020