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 Phytotoxicity of Nanoparticles by
Cover of the book Urban Planning in the Global South by
Cover of the book Séminaire de Probabilités XLVI by
Cover of the book Ancient Landscapes of Western North America by
Cover of the book Astrophysics Is Easy! by
Cover of the book Advanced Finite Element Simulation with MSC Marc by
Cover of the book Membrane Computing by
Cover of the book Pattern Recognition and Machine Intelligence by
Cover of the book Spatial Big Data Science by
Cover of the book Brain Arteriovenous Malformations by
Cover of the book Photons by
Cover of the book Homogeneous Catalysis with Renewables by
Cover of the book Modeling and Control for a Blended Wing Body Aircraft by
Cover of the book A Survey of Characteristic Engine Features for Technology-Sustained Pervasive Games by
Cover of the book Sustainability and the Humanities 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