Statistical Causal Inferences and Their Applications in Public Health Research
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Beschreibung
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 animportant reference.
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 animportant reference.
Includes software and data sets so readers may replicate analyses Contains much needed coverage of recent developments in causal inference Begins with an introduction to the concept of potential outcomes as applicable to causal inference concepts, models, and assumptions Includes supplementary material: sn.pub/extras
Autor*in
Hua He
Themen in »Statistical Causal Inferences and Their Applications in Public Health Research«
causal inference causal inference methodological development causal models for randomized trials causal parameters causal reasoning data analysis for public health data model development propensity score modeling
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“This is an excellent overview of statistical causal inferences and their applications in public health research. This book is strongly recommended to students in statistics, biostatistics, and computational biology as well as to researchers in public health and biomedical research.” (Hemang B. Panchal, Doody's Book Reviews, April, 2017)
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