Statistical Learning for Biomedical Data, Malley

Автор: Laird
Название: The fundamentals of modern statistical genetics
ISBN: 1441973370 ISBN-13(EAN): 9781441973375
Издательство: Springer
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Цена: 11878 р.
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Описание: This book covers the statistical models and methods that are used to understand human genetics, following the historical and recent developments of human genetics. Starting with Mendel’s first experiments to genome-wide association studies, the book describes how genetic information can be incorporated into statistical models to discover disease genes. All commonly used approaches in statistical genetics (e.g. aggregation analysis, segregation, linkage analysis, etc), are used, but the focus of the book is modern approaches to association analysis. Numerous examples illustrate key points throughout the text, both of Mendelian and complex genetic disorders. The intended audience is statisticians, biostatisticians, epidemiologists and quantitatively- oriented geneticists and health scientists wanting to learn about statistical methods for genetic analysis, whether to better analyze genetic data, or to pursue research in methodology. A background in intermediate level statistical methods is required. The authors include few mathematical derivations, and the exercises provide problems for students with a broad range of skill levels. No background in genetics is assumed.

Автор: Lee
Название: Statistical Methods for Survival Data Analysis, 4th Edition
ISBN: 1118095022 ISBN-13(EAN): 9781118095027
Издательство: Wiley
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Цена: 18050 р.
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Описание: Upgraded to reflect the latest research and software applications on the topic, this new edition continues to provide a comprehensive introduction to the statistical methods for analyzing survival data.

Автор: Walker, Jan Almond, Palo
Название: Interpreting statistical findings
ISBN: 0335235972 ISBN-13(EAN): 9780335235971
Издательство: McGraw-Hill
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Цена: 4803 р.
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Описание: This book is aimed at those studying and working in the field of health care, including nurses and the professions allied to medicine, who have little prior knowledge of statistics but for whom critical review of research is an essential skill.