Biostatistics Modeling and Public Health Applications
Study Design and Analysis Methodology in Health Sciences, Volume 1
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Beschreibung
This book provides an overview and compilation of contemporary topics and innovative approaches in biostatistical modeling through their applications to evidence-based public health research and decision-making. This book covers topics in 3 parts as: 1) Biostatistical Modeling, 2) Imaging Data Analysis, and 3) Public Health Applications.
Topics should appeal to both expert statisticians, as well as health researchers interested in biostatistical methodological applications in evidence-based health research. The book is a resourceful manual and can be used as an authoritative reference. The features covered in this book will appeal to researchers where public health research is being rigorously conducted.
This book provides an overview and compilation of contemporary topics and innovative approaches in biostatistical modeling through their applications to evidence-based public health research and decision-making. This book covers topics in 3 parts as: 1) Biostatistical Modeling, 2) Imaging Data Analysis, and 3) Public Health Applications.
Topics should appeal to both expert statisticians, as well as health researchers interested in biostatistical methodological applications in evidence-based health research. The book is a resourceful manual and can be used as an authoritative reference. The features covered in this book will appeal to researchers where public health research is being rigorously conducted.
Presents cutting-edge evidence-based public health research Includes biostatistical modeling with applications to real-world applications Provides theories and methods through their applications to evidence-based public health research and decision-making
Autor*in
Ding-Geng Chen
Themen in »Biostatistics Modeling and Public Health Applications«
Mathematical modelling statistical modelling spatial statistics Susceptible-Infected-Recovered (SIR) model maximum likelihood estimation causal inference survival analysis high-dimensional data