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Mendelian Randomization - Methods for Causal Inference Using Genetic Variants (Paperback, 2nd edition)
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Mendelian Randomization - Methods for Causal Inference Using Genetic Variants (Paperback, 2nd edition)
Series: Chapman & Hall/CRC Interdisciplinary Statistics
Expected to ship within 9 - 15 working days
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Mendelian Randomization: Methods For Causal Inference Using Genetic
Variants provides thorough coverage of the methods and practical
elements of Mendelian randomization analysis. It brings together
diverse aspects of Mendelian randomization from the fields of
epidemiology, statistics, genetics, and bioinformatics. Through
multiple examples, the first part of the book introduces the reader
to the concept of Mendelian randomization, showing how to perform
simple Mendelian randomization investigations and interpret the
results. The second part of the book addresses specific
methodological issues relevant to the practice of Mendelian
randomization, including robust methods, weak instruments,
multivariable methods, and power calculations. The authors present
the theoretical aspects of these issues in an easy-to-understand
way by using non-technical language. The last part of the book
examines the potential for Mendelian randomization in the future,
exploring both methodological and applied developments. Features
Offers first-hand, in-depth guidance on Mendelian randomization
from leaders in the field Makes the diverse aspects of Mendelian
randomization understandable to newcomers Illustrates technical
details using data from applied analyses Discusses possible future
directions for research involving Mendelian randomization Software
code is provided in the relevant chapters and is also available at
the supplementary website This book gives epidemiologists,
statisticians, geneticists, and bioinformaticians the foundation to
understand how to use genetic variants as instrumental variables in
observational data. New in Second Edition: The second edition of
the book has been substantially re-written to reduce the amount of
technical content, and emphasize practical consequences of
theoretical issues. Extensive material on the use of two-sample
Mendelian randomization and publicly-available summarized data has
been added. The book now includes several real-world examples that
show how Mendelian randomization can be used to address questions
of disease aetiology, target validation, and drug development
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