Statistical Causal Inferences and Their Applications in Public Health Research

Nonfiction, Health & Well Being, Medical, Reference, Biostatistics, Science & Nature, Mathematics, Science, Biological Sciences
Cover of the book Statistical Causal Inferences and Their Applications in Public Health Research by , Springer International Publishing
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: ISBN: 9783319412597
Publisher: Springer International Publishing Publication: October 26, 2016
Imprint: Springer Language: English
Author:
ISBN: 9783319412597
Publisher: Springer International Publishing
Publication: October 26, 2016
Imprint: Springer
Language: English

This book compiles and presents new developments in statistical causal inference. The accompanying data and computer programs are publicly available so readers may replicate the model development and data analysis presented in each chapter. In this way, methodology is taught so that readers may implement it directly. The book brings together experts engaged in causal inference research to present and discuss recent issues in causal inference methodological development. This is also a timely look at causal inference applied to scenarios that range from clinical trials to mediation and public health research more broadly. In an academic setting, this book will serve as a reference and guide to a course in causal inference at the graduate level (Master's or Doctorate). It is particularly relevant for students pursuing degrees in statistics, biostatistics, and computational biology. Researchers and data analysts in public health and biomedical research will also find this book to be an important reference. 

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

This book compiles and presents new developments in statistical causal inference. The accompanying data and computer programs are publicly available so readers may replicate the model development and data analysis presented in each chapter. In this way, methodology is taught so that readers may implement it directly. The book brings together experts engaged in causal inference research to present and discuss recent issues in causal inference methodological development. This is also a timely look at causal inference applied to scenarios that range from clinical trials to mediation and public health research more broadly. In an academic setting, this book will serve as a reference and guide to a course in causal inference at the graduate level (Master's or Doctorate). It is particularly relevant for students pursuing degrees in statistics, biostatistics, and computational biology. Researchers and data analysts in public health and biomedical research will also find this book to be an important reference. 

More books from Springer International Publishing

Cover of the book Endometriosis by
Cover of the book Statistical Disclosure Control for Microdata by
Cover of the book Multiagent System Technologies by
Cover of the book Heading North by
Cover of the book Analog-and-Algorithm-Assisted Ultra-low Power Biosignal Acquisition Systems by
Cover of the book Video Astronomy on the Go by
Cover of the book The Calculus of Life by
Cover of the book Enhancing Fieldwork Learning Using Mobile Technologies by
Cover of the book Transients for Electrical Engineers by
Cover of the book Reflection Positivity by
Cover of the book Advances in Human Factors in Cybersecurity by
Cover of the book Siberian Traps and Pt-Cu-Ni Deposits in the Noril’sk Area by
Cover of the book Dementia Care by
Cover of the book Laser-Plasma Interactions and Applications by
Cover of the book Big Data Analytics: A Management Perspective by
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy