How Long to Read Mixture Modelling for Medical and Health Sciences

How Long Does it Take to Read Mixture Modelling for Medical and Health Sciences?

It takes the average reader 5 hours and 4 minutes to read Mixture Modelling for Medical and Health Sciences by SHU KAY. XIANG NG (LIMING. YAU, KELVIN KAI WING.)

Assuming a reading speed of 250 words per minute. Learn more

Description

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. Features An in-depth account of the most up-to-date mixture modelling techniques from auser perspective. Extensive real-life examples - from typical daily problems to complex data modelling. Emphasis on the use of a wide variety of component densities for statistical modelling. Coverage of the latest random-effects models in modelling complex correlated data. An accompanying website to provide supplementary materials, including software and detailed programming code, and links to available data sources. Provision of R and Fortran code for readers who want to do analysis of their own data using mixture models. Shu-Kay Angus Ng is Professor of Biostatistics in the School of Medicine at the Griffith University, Australia. Dr Ng has published extensively on his research interests, which include cluster analysis, pattern recognition, random-effects modelling, and survival analysis. Liming Xiang is Associate Professor of Statistics in the School of Physical & Mathematical Sciences at the Nanyang Technological University, Singapore. Her research interests include survival analysis, longitudinal/clustered data analysis and mixture models. Kelvin Kai-wing Yau is Professor of Statistics in the Department of Management Sciences at the City University of Hong Kong. He has been involved in various interdisciplinary research projects, with journal publications in statistics, medical and health science journals on topics such as mixed effects models, survival analysis and statistical modelling in general.

How long is Mixture Modelling for Medical and Health Sciences?

Mixture Modelling for Medical and Health Sciences by SHU KAY. XIANG NG (LIMING. YAU, KELVIN KAI WING.) is 302 pages long, and a total of 76,104 words.

This makes it 102% the length of the average book. It also has 93% more words than the average book.

How Long Does it Take to Read Mixture Modelling for Medical and Health Sciences Aloud?

The average oral reading speed is 183 words per minute. This means it takes 6 hours and 55 minutes to read Mixture Modelling for Medical and Health Sciences aloud.

What Reading Level is Mixture Modelling for Medical and Health Sciences?

Mixture Modelling for Medical and Health Sciences is suitable for students ages 12 and up.

Note that there may be other factors that effect this rating besides length that are not factored in on this page. This may include things like complex language or sensitive topics not suitable for students of certain ages.

When deciding what to show young students always use your best judgement and consult a professional.

Where Can I Buy Mixture Modelling for Medical and Health Sciences?

Mixture Modelling for Medical and Health Sciences by SHU KAY. XIANG NG (LIMING. YAU, KELVIN KAI WING.) is sold by several retailers and bookshops. However, Read Time works with Amazon to provide an easier way to purchase books.

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