Statistical Methods For Dynamic Disease Screening And Spatio Temporal Disease Surveillance
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Statistical Methods For Dynamic Disease Screening And Spatio Temporal Disease Surveillance
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Author : Peihua Qiu
language : en
Publisher: CRC Press
Release Date : 2024-06-18
Statistical Methods For Dynamic Disease Screening And Spatio Temporal Disease Surveillance written by Peihua Qiu and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-18 with Mathematics categories.
Disease screening and disease surveillance (DSDS) constitute two critical areas in public health, each presenting distinctive challenges primarily due to their sequential decision-making nature and complex data structures. Statistical Methods for Dynamic Disease Screening and Spatio-Temporal Disease Surveillance explores numerous recent analytic methodologies that enhance traditional techniques. The author, a prominent researcher specializing in innovative sequential decision-making techniques, demonstrates how these novel methods effectively address the challenges of DSDS. After a concise introduction that lays the groundwork for comprehending the challenges inherent in DSDS, the book delves into fundamental statistical concepts and methods relevant to DSDS. This includes exploration of statistical process control (SPC) charts specifically crafted for sequential decision-making purposes. The subsequent chapters systematically outline recent advancements in dynamic screening system (DySS) methods, fine-tuned for effective disease screening. Additionally, the text covers both traditional and contemporary analytic methods for disease surveillance. It further introduces two recently developed R packages designed for implementing DySS methods and spatio-temporal disease surveillance techniques pioneered by the author's research team. Features • Presents Recent Analytic Methods for DSDS: The book introduces analytic methods for DSDS based on SPC charts. These methods effectively utilize all historical data, accommodating the complex data structure inherent in sequential decision-making processes. • Introduces Recent R Packages: Two recent R packages, DySS and SpTe2M, are introduced. The book not only presents these packages but also demonstrates key DSDS methods using them. • Examines Recent Research Results: The text delves into the latest research findings across various domains, including dynamic disease screening, nonparametric spatio-temporal data modeling and monitoring, and spatio-temporal disease surveillance. • Accessible Description of Methods: Major methods are described in a manner accessible to individuals without advanced knowledge in mathematics and statistics. The goal is to facilitate a clear understanding of ideas and easy implementation. • Real-Data Examples: To aid comprehension, the book provides several real-data examples illustrating key concepts and methods. • Hands-on Exercises: Each chapter includes exercises to encourage hands-on practice, allowing readers to engage directly with the presented methods.
Monitoring The Health Of Populations
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Author : Ron Brookmeyer
language : en
Publisher: Oxford University Press
Release Date : 2003-10-23
Monitoring The Health Of Populations written by Ron Brookmeyer and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-10-23 with Medical categories.
Public health faces critical challenges ranging from outbreaks of new and old pathogens to the threat of bioterrorism and the impact of lifestyle and environmental changes on health. Modern tools of health surveillance and sound statistical practices are essential for meeting these challenges and providing accurate warnings about real public health threats without wasting resources on false alarms. Advances in statistical techniques, computing power and the Internet have led to many new approaches to monitoring population health, analyzing the data, and rapidly sharing it. This text explores the critical issues in the statistical analysis and interpretation of public health surveillance data. It covers statistical methods for detecting disease outbreaks and clusters, the use of survey methods, interpreting time trends and geographic patterns, exploratory statistical analysis of surveillance data, and web-based health reporting systems for the rapid detection of public health problems, among other topics. The methodological approaches are illustrated in discussions of several current public health issues, including the HIV/AIDS epidemic, anthrax, health effects of particulate air pollution, and trends in prostate cancer. The methods are broadly applicable to surveillance systems and registries for numerous health conditions, e.g. infectious diseases, chronic diseases, adverse drug reactions. The book provides numerous illustrations, worked examples, and practical information for actually implementing the methods. It will serve as a reference for public health practitioners and as a textbook for courses on disease surveillance taken by students of statistics biostatistics, epidemiology or public health.
Applied Microbiome Statistics
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Author : Yinglin Xia
language : en
Publisher: CRC Press
Release Date : 2024-07-22
Applied Microbiome Statistics written by Yinglin Xia and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-22 with Mathematics categories.
This unique book officially defines microbiome statistics as a specific new field of statistics and addresses the statistical analysis of correlation, association, interaction, and composition in microbiome research. It also defines the study of the microbiome as a hypothesis-driven experimental science and describes two microbiome research themes and six unique characteristics of microbiome data, as well as investigating challenges for statistical analysis of microbiome data using the standard statistical methods. This book is useful for researchers of biostatistics, ecology, and data analysts. Presents a thorough overview of statistical methods in microbiome statistics of parametric and nonparametric correlation, association, interaction, and composition adopted from classical statistics and ecology and specifically designed for microbiome research. Performs step-by-step statistical analysis of correlation, association, interaction, and composition in microbiome data. Discusses the issues of statistical analysis of microbiome data: high dimensionality, compositionality, sparsity, overdispersion, zero-inflation, and heterogeneity. Investigates statistical methods on multiple comparisons and multiple hypothesis testing and applications to microbiome data. Introduces a series of exploratory tools to visualize composition and correlation of microbial taxa by barplot, heatmap, and correlation plot. Employs the Kruskal–Wallis rank-sum test to perform model selection for further multi-omics data integration. Offers R code and the datasets from the authors’ real microbiome research and publicly available data for the analysis used. Remarks on the advantages and disadvantages of each of the methods used.
Development Of Gene Therapies
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Author : Avery McIntosh
language : en
Publisher: CRC Press
Release Date : 2024-05-23
Development Of Gene Therapies written by Avery McIntosh and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-23 with Mathematics categories.
Cell and gene therapies have become the third major drug modality in pharmaceutical medicine of the 21st century after low molecular weight and antibody drugs. The gene therapy (GTx) field is rapidly advancing, and yet there are still fundamental scientific questions that remain to be answered. Development of GTx products poses unique challenges and opportunities for drug developers. However, there is lack of a systematic exposition of the GTx product development and the pivotal role of the biostatistician in this process. Development of Gene Therapies: Strategic, Scientific, and Regulatory, and Access Considerations attempts to summarize the current state-of-the-art strategic, scientific, statistical, and regulatory aspects of GTx development. Intended to provide an exposition to the GTx new product development through peer-reviewed papers written by subject matter experts in this emerging field, this book will be useful for researchers in gene therapy drug development, biostatisticians, regulators, patient advocates, graduate students, and the finance and business development community . Key Features: A collection of papers covering a wide spectrum of topics in gene therapies (GTx), written by leading subject matter experts An exposition of the core principles of GTx product development, emerging business models, industry standards, best practices, and regulatory pathways An exposition of statistical and innovative modeling tools for design and analysis of clinical trials of GTx Insights into commercial models, access hurdles, and health economics of gene therapies Case studies of successful GTx approvals from core team members that developed the first two FDA-approved AAV gene therapies: Luxturna and Zolgensma A discussion of potential benefits and hurdles to be overcome for GTx in coming years from a multi-stakeholder perspective
Causal Inference In Pharmaceutical Statistics
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Author : Yixin Fang
language : en
Publisher: CRC Press
Release Date : 2024-06-24
Causal Inference In Pharmaceutical Statistics written by Yixin Fang and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-24 with Mathematics categories.
Causal Inference in Pharmaceutical Statistics introduces the basic concepts and fundamental methods of causal inference relevant to pharmaceutical statistics. This book covers causal thinking for different types of commonly used study designs in the pharmaceutical industry, including but not limited to randomized controlled clinical trials, longitudinal studies, singlearm clinical trials with external controls, and real-world evidence studies. The book starts with the central questions in drug development and licensing, takes the reader through the basic concepts and methods via different study types and through different stages, and concludes with a roadmap to conduct causal inference in clinical studies. The book is intended for clinical statisticians and epidemiologists working in the pharmaceutical industry. It will also be useful to graduate students in statistics, biostatistics, and data science looking to pursue a career in the pharmaceutical industry. Key Features: Causal inference book for clinical statisticians in the pharmaceutical industry Introductory level on the most important concepts and methods Align with FDA and ICH guidance documents Across different stages of clinical studies: plan, design, conduct, analysis, and interpretation Cover a variety of commonly used study designs
Bayesian Precision Medicine
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Author : Peter F. Thall
language : en
Publisher: CRC Press
Release Date : 2024-05-07
Bayesian Precision Medicine written by Peter F. Thall and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-07 with Mathematics categories.
Bayesian Precision Medicine presents modern Bayesian statistical models and methods for identifying treatments tailored to individual patients using their prognostic variables and predictive biomarkers. The process of evaluating and comparing treatments is explained and illustrated by practical examples, followed by a discussion of causal analysis and its relationship to statistical inference. A wide array of modern Bayesian clinical trial designs are presented, including applications to many oncology trials. The later chapters describe Bayesian nonparametric regression analyses of datasets arising from multistage chemotherapy for acute leukemia, allogeneic stem cell transplantation, and targeted agents for treating advanced breast cancer. Features: Describes the connection between causal analysis and statistical inference Reviews modern personalized Bayesian clinical trial designs for dose-finding, treatment screening, basket trials, enrichment, incorporating historical data, and confirmatory treatment comparison, illustrated by real-world applications Presents adaptive methods for clustering similar patient subgroups to improve efficiency Describes Bayesian nonparametric regression analyses of real-world datasets from oncology Provides pointers to software for implementation Bayesian Precision Medicine is primarily aimed at biostatisticians and medical researchers who desire to apply modern Bayesian methods to their own clinical trials and data analyses. It also might be used to teach a special topics course on precision medicine using a Bayesian approach to postgraduate biostatistics students. The main goal of the book is to show how Bayesian thinking can provide a practical scientific basis for tailoring treatments to individual patients.
Association Models In Epidemiology
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Author : Hongjie Liu
language : en
Publisher: CRC Press
Release Date : 2024-08-05
Association Models In Epidemiology written by Hongjie Liu and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-05 with Medical categories.
Association Models in Epidemiology: Study Designs, Modeling Strategies, and Analytic Methods is written by an epidemiologist for graduate students, researchers, and practitioners who will use regression techniques to analyze data. It focuses on association models rather than prediction models. The book targets students and working professionals who lack bona fide modeling experts but are committed to conducting appropriate regression analyses and generating valid findings from their projects. This book aims to offer detailed strategies to guide them in modeling epidemiologic data. Features Custom-Tailored Models: Discover association models specifically designed for epidemiologic study designs. Epidemiologic Principles in Action: Learn how to apply and translate epidemiologic principles into regression modeling techniques. Model Specification Guidance: Get expert guidance on model specifications to estimate exposure-outcome associations, accurately controlling for confounding bias. Accessible Language: Explore regression intricacies in user-friendly language, accompanied by real-world examples that make learning easier. Step-by-Step Approach: Follow a straightforward step-by-step approach to master strategies and procedures for analysis. Rich in Examples: Benefit from 120 examples, 77 figures, 86 tables, and 174 SAS® outputs with annotations to enhance your understanding. Crafted for two primary audiences, this text benefits graduate epidemiology students seeking to understand how epidemiologic principles inform modeling analyses and public health professionals conducting independent analyses in their work. Therefore, this book serves as a textbook in the classroom and as a reference book in the workplace. A wealth of supporting material is available for download from the book’s CRC Press webpage. Upon completing this text, readers should gain confidence in accurately estimating associations between risk factors and outcomes, controlling confounding bias, and assessing effect modification.
Monitoring The Health Of Populations
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Author : Ron Brookmeyer
language : en
Publisher: Oxford University Press
Release Date : 2004
Monitoring The Health Of Populations written by Ron Brookmeyer and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Medical categories.
This text explores the critical issues in the statistical analysis and interpretation of public health surveillance data. It covers statistical methods for detecting disease outbreaks and clusters, the use of survey methods and interpreting time trends and geographic patterns, among other topics.
Early Warning For Infectious Disease Outbreak
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Author : Weizhong Yang
language : en
Publisher: Academic Press
Release Date : 2017-04-25
Early Warning For Infectious Disease Outbreak written by Weizhong Yang and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-04-25 with Medical categories.
Early Warning for Infectious Disease Outbreak: Theory and Practice is divided into three parts, with the first section introducing basic theory and key technologies of early warning and the basic principles of infectious disease surveillance. The second section introduces the technical details in the process of establishment, operation and usage of CIDARS and Pudong Syndromic Surveillance and the Early Warning System of the Shanghai World Expo. The third part explores the study of early warning technology, collecting some useful exploration in the fields of infectious diseases involving sentinel setting, data analysis, influence factors study, calculation and evaluation of early warning models. Provide insights into the theory and practice of early warning systems that have been evaluated and shown to be effective Presents a synopsis of current state-of-the-art practices and a starting point for the development and evaluation of new methods Covers applied research and complete case studies that focus on local, regional, national and international implementation Includes techniques from other fields, such as intelligence and engineering Explores future innovations in biosurveillance, including advances in analytical methods, modeling and simulation Addresses policy and organizational issues related to the construction of biosurveillance systems
Bayes Rules
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Author : Alicia A. Johnson
language : en
Publisher: CRC Press
Release Date : 2022-03-03
Bayes Rules written by Alicia A. Johnson and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-03 with Mathematics categories.
Praise for Bayes Rules!: An Introduction to Applied Bayesian Modeling “A thoughtful and entertaining book, and a great way to get started with Bayesian analysis.” Andrew Gelman, Columbia University “The examples are modern, and even many frequentist intro books ignore important topics (like the great p-value debate) that the authors address. The focus on simulation for understanding is excellent.” Amy Herring, Duke University “I sincerely believe that a generation of students will cite this book as inspiration for their use of – and love for – Bayesian statistics. The narrative holds the reader’s attention and flows naturally – almost conversationally. Put simply, this is perhaps the most engaging introductory statistics textbook I have ever read. [It] is a natural choice for an introductory undergraduate course in applied Bayesian statistics." Yue Jiang, Duke University “This is by far the best book I’ve seen on how to (and how to teach students to) do Bayesian modeling and understand the underlying mathematics and computation. The authors build intuition and scaffold ideas expertly, using interesting real case studies, insightful graphics, and clear explanations. The scope of this book is vast – from basic building blocks to hierarchical modeling, but the authors’ thoughtful organization allows the reader to navigate this journey smoothly. And impressively, by the end of the book, one can run sophisticated Bayesian models and actually understand the whys, whats, and hows.” Paul Roback, St. Olaf College “The authors provide a compelling, integrated, accessible, and non-religious introduction to statistical modeling using a Bayesian approach. They outline a principled approach that features computational implementations and model assessment with ethical implications interwoven throughout. Students and instructors will find the conceptual and computational exercises to be fresh and engaging.” Nicholas Horton, Amherst College An engaging, sophisticated, and fun introduction to the field of Bayesian statistics, Bayes Rules!: An Introduction to Applied Bayesian Modeling brings the power of modern Bayesian thinking, modeling, and computing to a broad audience. In particular, the book is an ideal resource for advanced undergraduate statistics students and practitioners with comparable experience. Bayes Rules! empowers readers to weave Bayesian approaches into their everyday practice. Discussions and applications are data driven. A natural progression from fundamental to multivariable, hierarchical models emphasizes a practical and generalizable model building process. The evaluation of these Bayesian models reflects the fact that a data analysis does not exist in a vacuum. Features • Utilizes data-driven examples and exercises. • Emphasizes the iterative model building and evaluation process. • Surveys an interconnected range of multivariable regression and classification models. • Presents fundamental Markov chain Monte Carlo simulation. • Integrates R code, including RStan modeling tools and the bayesrules package. • Encourages readers to tap into their intuition and learn by doing. • Provides a friendly and inclusive introduction to technical Bayesian concepts. • Supports Bayesian applications with foundational Bayesian theory.