Statistical Causal Inferences and Their Applications in Public Health Research (Hardcover, 1st ed. 2016)

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.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Series:	ICSA Book Series in Statistics
Release date:	November 2016
First published:	2016
Editors:	Hua He • Pan Wu • Ding-Geng (Din) Chen
Dimensions:	235 x 155 x 27mm (L x W x T)
Format:	Hardcover
Pages:	321
Edition:	1st ed. 2016
ISBN-13:	978-3-319-41257-3
Categories:	Books > Science & Mathematics > Mathematics > Probability & statistics Books > Medicine > General issues > Public health & preventive medicine > General Books > Science & Mathematics > Biology, life sciences > Life sciences: general issues > General Promotions
LSN:	3-319-41257-4
Barcode:	9783319412573

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