Modern Inference Based on Health-Related Markers

Biomarkers and Statistical Decision Making

Albert Vexler, Jihnhee Yu, Jiaojiao Zhou, Albert Vexler, Jihnhee Yu, Jiaojiao Zhou

• Publisher: Academic Press
• Year: 2024
• Print ISBN:
  9780128152478
• eBook ISBN:
  9780128152485
• Topic: Medicine
• Subtopic: Pharmaceutical, Biotechnology & Healthcare Industry

Modern Inference Based on Health Related Markers: Biomarkers and Statistical Decision Making provides a compendium of biomarkers based methodologies for respective health related fields and health related marker-specific biostatistical techniques. These methodologies may be applied to various problems encountered in medical and epidemiological studies. This book introduces correct and efficient testing mechanisms including procedures based on bootstrap and permutation methods with the aim of making these techniques assessable to practical researchers. In the biostatistical aspect, it describes how to correctly state testing problems, but it also includes novel results, which have appeared in current statistical publications. The book discusses also modern applied statistical developments that consider data-driven techniques, including empirical likelihood methods and other simple and efficient methods to derive statistical tools for use in health related studies. The title is a valuable source for biostaticians, practitioners, theoretical and applied investigators, and several members of the biomedical field who are interested in learning more about efficient evidence-based inference incorporating several forms of markers measurements. - Combines modern epidemiological and public health discoveries with cutting-edge biostatistical tools, including relevant software codes, offering one full package to meet the demand of practical investigators - Includes the emerging topics from real health fields in order to display recent advances and trends in Biomarkers and associated Decision Making areas - Written by researchers who are leaders of Epidemiological and Biostatistical fields, presenting up-to-date investigations related to the measuring health issues, emerging fields of biomarkers, designing health studies and their implementations, clinical trials and their practices and applications, different aspects of genetic markers

Table of contents

• Title of Book
• Cover image
• Title page
• Table of Contents
• Copyright
• Contributors
• Preface
• Chapter 1 An array of statistical concepts and tools for handling challenging data
• Chapter 2 A review of expected P-values and their applications in biomarkers studies
• Chapter 3 Latent class modeling approaches for studying the effects of chemical mixtures on disease risk
• Chapter 4 Incomplete data in health studies
• Chapter 5 An introduction to biomarkers in translational research (2023)
• Chapter 6 Collection and handling of biomarkers of inorganic arsenic exposure in statistical analyses
• Chapter 7 Efficient sample pooling strategies for COVID-19 data gathering
• Chapter 8 Implications of childhood neighborhood quality for young adult parasympathetic reactivity
• Chapter 9 Application of adaptive designs in clinical research
• Chapter 10 Comparison of multivariate pooling strategies based on skewed data in light of the receiver operating characteristic curve analysis
• Chapter 11 ROC methods in biomarker development
• Chapter 12 Introduction of diffusion tensor imaging data: An overview for novice users
• Chapter 13 Genome-driven cancer site characterization: An overview of the hidden genome model
• Chapter 14 Thalamic volumetry via deep learning as an imaging biomarker in multiple sclerosis
• Index