Biostatistics Modeling and Public Health Applications

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

Auteur

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 research chair in biostatistics at the University of Pretoria, an honorary professor at the University of KwaZulu-Natal, South Africa. He is a senior biostatistics consultant for biopharmaceuticals and government agencies with extensive expertise in biostatistics, clinical trials, and public health statistics and data sciences. Dr. Chen has more than 200 referred professional publications, co-authored/co-edited 40 books on clinical trial methodology, meta-analysis, data science, causal inference, and public health research.

DCarlos A. 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 tests for high-dimensionality and the application of Multivariate Analysis techniques to Statistical Disclosure Control problems. Carlos A. Coelho currently serves in the Editorial Boards of the Journal of Statistical Theory and Practice and the American Journal of Mathematical and Management Sciences. 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). Currently, Carlos A. Coelho also serves as President of Fulbrighters Portugal, the Portuguese Fulbright Alumni Association.

Contenu

.- Bootstrap calibrated tests for average bioequivalence and scaled average bioequivalence.
.- Hypothesis Testing within Bayesian Inference "Regression Estimation for Length-Biased Data:A Review and Comparative Study".
.- "Nonparametric Methods for Incomplete Multivariate Data: Applications to Quality of Life Outcomes".
.- Geostatistical Analysis of Under-Five Children Mortality and Associated Factors Across Sub-Saharan African Countries.
.- SEIRD Mathematical Modelling of Malaria Transmission Dynamics in Ethiopia.
.- Robust Principal Component Analysis for Retinal Image Enhancement.
.- "Estimating Average and Individual Treatment Effects in the Presence of Time-Dependent Covariates".
.- "Detection of Quadratic Interactions in Brain Functional Connectivity".
.- "Variable selection in the generalized semiparametric longitudinal model and HIV analysis".
.- Survey design effect in the prediction of events for categorical health outcomes through regression methods: Evidence from Malawi under-five mortality survey data; 2000-2016.
.- Survey design effect in the prediction of events for categorical health outcomes through regression methods: Evidence from Malawi under-five mortality survey data; 2000-2016.
.- Issues in Multivariate Spatial Analysis of Multiple Diseases Using Complex Health Survey Data.