Statistical Modeling and Applications

This book provides an overview and compilation of emerging topics in mathematical and statistical theories and methods, through their applications to evidence-based public health research and decision-making. Each contributor are researchers around the globe, engaged in mathematical and statistical methods and applications to present their current and cutting-edge research achievements. All chapters share their data and computing program, to promote their developed mathematical and statistical methods in association to solve real-life applications.

Evidence-based public health research and applications call for modern mathematical and statistical methods. This book covers topics in 3 parts as: 1) Mathematical Modeling, where 9 chapters are included, 2) Statistical Modelling, where 10 chapters are included, and 3) Real-World Applications, where 7 chapters are included.

Topics included, should appeal to both expert mathematicians and statisticians as well as health researchers interested in methodological applications in evidence-based health research. The book will be 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.

Carlos Coelho is a Full Professor of Statistics at the Mathematics Department of NOVA School of Science and Technology of NOVA University of Lisbon. He holds a Ph.D. in Biostatistics by The University of Michigan, Ann Arbor, MI, U.S.A., where he was a Fulbrighter. His main area of research is Multivariate Analysis, namely the development of likelihood ratio tests for elaborate covariance structures and for MANOVA models, also with elaborate covariance structures, together with the study of the exact distribution and the development of near-exact distributions for the associated test statistics. Related with this area, other areas of interest are Mathematical Statistics and Distribution Theory, as well as Estimation, Univariate and Multivariate Linear, Generalized Linear and Mixed Models. More recently, he also got interested in tests for high-dimensionality and the application of Multivariate Analysis techniques to Statistical Disclosure Control problems. Carlos A.Coelho has served as Associate Editor in the Editorial Boards of REVSTAT-Statistical Journal, the Journal of Interdisciplinary Mathematics and the Journal of Applied Statistics and currently serves in the Editorial Boards of the Journal of Statistical Theory and Practice, the American Journal of Mathematical and Management Sciences and Discussiones Mathematicae—Probability and Statistics. He is also Associate Editor of the Springer Book series “Emerging Topics in Statistics and Biostatistics” and a member of the International Council of the “Business World” Library of the Tsenov Academy of Economics (Svishtov, Bulgaria).

Ding-Geng Chen is a fellow of the American Statistical Association and is currently the executive director and professor in biostatistics at the College of Health Solutions, Arizona State University. He is also an extraordinary professor and the SARChI in biostatistics at the University of Pretoria, an honorary professor at the University of KwaZulu-Natal, South Africa. Dr. Chen was the Karl E. Peace Endowed Eminent Scholar Chair in Biostatistics at Georgia Southern University. He is a senior biostatistics consultant for biopharmaceuticals and government agencies with extensive expertise in biostatistics, clinical trials, and public health statistics. Dr. Chen has more than 200 referred professional publications and co-authored and co-edited 35 books on clinical trial methodology, meta-analysis, data science, causal inference, and public health research.