Modern Biostatistical Methods for Evidence-Based Global Health Research

Modern Biostatistical Methods for Evidence-Based Global Health Research
Author: Ding-Geng (Din) Chen
Publisher: Springer Nature
Total Pages: 489
Release: 2022-11-25
Genre: Medical
ISBN: 3031110129
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This book provides an overview of the emerging topics in biostatistical theories and methods through their applications to evidence-based global health research and decision-making. It brings together some of the top scholars engaged in biostatistical method development on global health to highlight and describe recent advances in evidence-based global health applications. The volume is composed of five main parts: data harmonization and analysis; systematic review and statistical meta-analysis; spatial-temporal modeling and disease mapping; Bayesian statistical modeling; and statistical methods for longitudinal data or survival data. It is designed to be illuminating and valuable to both expert biostatisticians and to health researchers engaged in methodological applications in evidence-based global health research. It is particularly relevant to countries where global health research is being rigorously conducted.

Modern Statistical Methods for Health Research

Modern Statistical Methods for Health Research
Author: Yichuan Zhao
Publisher: Springer Nature
Total Pages: 506
Release: 2021-10-14
Genre: Medical
ISBN: 3030724379
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This book brings together the voices of leading experts in the frontiers of biostatistics, biomedicine, and the health sciences to discuss the statistical procedures, useful methods, and novel applications in biostatistics research. It also includes discussions of potential future directions of biomedicine and new statistical developments for health research, with the intent of stimulating research and fostering the interactions of scholars across health research related disciplines. Topics covered include: Health data analysis and applications to EHR data Clinical trials, FDR, and applications in health science Big network analytics and its applications in GWAS Survival analysis and functional data analysis Graphical modelling in genomic studies The book will be valuable to data scientists and statisticians who are working in biomedicine and health, other practitioners in the health sciences, and graduate students and researchers in biostatistics and health.

Statistical Methods for Global Health and Epidemiology

Statistical Methods for Global Health and Epidemiology
Author: Xinguang Chen
Publisher: Springer Nature
Total Pages: 420
Release: 2020-04-13
Genre: Medical
ISBN: 3030352609
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This book examines statistical methods and models used in the fields of global health and epidemiology. It includes methods such as innovative probability sampling, data harmonization and encryption, and advanced descriptive, analytical and monitory methods. Program codes using R are included as well as real data examples. Contemporary global health and epidemiology involves a myriad of medical and health challenges, including inequality of treatment, the HIV/AIDS epidemic and its subsequent control, the flu, cancer, tobacco control, drug use, and environmental pollution. In addition to its vast scales and telescopic perspective; addressing global health concerns often involves examining resource-limited populations with large geographic, socioeconomic diversities. Therefore, advancing global health requires new epidemiological design, new data, and new methods for sampling, data processing, and statistical analysis. This book provides global health researchers with methods that will enable access to and utilization of existing data. Featuring contributions from both epidemiological and biostatistical scholars, this book is a practical resource for researchers, practitioners, and students in solving global health problems in research, education, training, and consultation.

Statistical Methods for Global Health and Epidemiology

Statistical Methods for Global Health and Epidemiology
Author:
Publisher:
Total Pages: 413
Release: 2020
Genre: Electronic books
ISBN: 9783030352615
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This book examines statistical methods and models used in the fields of global health and epidemiology. It includes methods such as innovative probability sampling, data harmonization and encryption, and advanced descriptive, analytical and monitory methods. Program codes using R are included as well as real data examples. Contemporary global health involves a myriad of medical and health challenges, including inequality of treatment, the HIV/AIDS epidemic and its subsequent control, the flu, tobacco control, drug use, and environmental pollution. In addition to its vast scales and telescopic perspective, addressing global health concerns often involves examining resource-limited populations with large geographic, socioeconomic diversities. Therefore, advancing global health requires new epidemiological design, new data, and new methods for sampling, data processing, and statistical analysis. This book provides global health researchers with methods that will enable access to and utilization of existing data. Featuring contributions from both epidemiological and biostatistical scholars, this book is a practical resource for researchers, practitioners, and students in solving global health problems in research, education, training, and consultation.

Biostatistics Modeling and Public Health Applications

Biostatistics Modeling and Public Health Applications
Author: Ding-Geng Din Chen
Publisher: Springer
Total Pages: 0
Release: 2024-11-03
Genre: Mathematics
ISBN: 9783031696893
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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.

Introductory Biostatistics for the Health Sciences

Introductory Biostatistics for the Health Sciences
Author: Michael R. Chernick
Publisher: John Wiley & Sons
Total Pages: 426
Release: 2003-06-24
Genre: Mathematics
ISBN: 0471458651
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"Introductory Biostatistics for the Health Sciences" ist eine fundierte Einführung in die Biostatistik und ihre Anwendungsgebiete. Der Band richtet sich vorwiegend an Mediziner und Statistiker. Theorie und Praxis stehen im ausgewogenen Verhältnis, d.h. praktische Anwendungen werden, wo nötig, durch den theoretischen Hintergrund ergänzt. Der Schwerpunkt liegt eindeutig auf der praktischen Anwendung. Der Band geht auch auf jüngste Fortschritte bei der Bootstrap-, Outlier- und Meta-Analyse ein, Themen, die in der Regel in Konkurrenzwerken, nicht behandelt werden. Mit einer Fülle von Übungsaufgaben. Auch Statistiksoftware wird ausführlich besprochen.

Modern Issues and Methods in Biostatistics

Modern Issues and Methods in Biostatistics
Author: Mark Chang
Publisher: Springer Science & Business Media
Total Pages: 316
Release: 2011-07-15
Genre: Medical
ISBN: 144199842X
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Classic biostatistics, a branch of statistical science, has as its main focus the applications of statistics in public health, the life sciences, and the pharmaceutical industry. Modern biostatistics, beyond just a simple application of statistics, is a confluence of statistics and knowledge of multiple intertwined fields. The application demands, the advancements in computer technology, and the rapid growth of life science data (e.g., genomics data) have promoted the formation of modern biostatistics. There are at least three characteristics of modern biostatistics: (1) in-depth engagement in the application fields that require penetration of knowledge across several fields, (2) high-level complexity of data because they are longitudinal, incomplete, or latent because they are heterogeneous due to a mixture of data or experiment types, because of high-dimensionality, which may make meaningful reduction impossible, or because of extremely small or large size; and (3) dynamics, the speed of development in methodology and analyses, has to match the fast growth of data with a constantly changing face. This book is written for researchers, biostatisticians/statisticians, and scientists who are interested in quantitative analyses. The goal is to introduce modern methods in biostatistics and help researchers and students quickly grasp key concepts and methods. Many methods can solve the same problem and many problems can be solved by the same method, which becomes apparent when those topics are discussed in this single volume.

Medical Biostatistics, Second Edition

Medical Biostatistics, Second Edition
Author: Abhaya Indrayan
Publisher: Chapman and Hall/CRC
Total Pages: 0
Release: 2008-03-10
Genre: Mathematics
ISBN: 9781584888871
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Emphasizing statistical concepts used in medicine, the interpretation of methods, and applications, Medical Biostatistics, Second Edition shows how biostatistical methods are important tools in managing uncertainties in medicine and the health sciences. With coverage ranging from elementary topics, such as mean and standard deviation, to advanced approaches, such as logistic regression and multivariate methods, this edition is even more far-reaching in scope than its predecessor. New to the Second Edition Full chapters on clinical trials, observational studies, laboratory experiments, survival analysis, and logistic regression A new chapter on clinimetrics and evidence-based medicine Expanded discussions on epistemic uncertainties, crossover designs, equivalence trials and studies, hazard functions, and the log-rank test The introduction of research evidence, multilevel regression, classification, and regression trees at an elementary level Sample size formulas for relative risk, odds ratio, and survival studies Numerous additional examples from contemporary medical literature Numbered steps for the many procedures and remarks Requiring only high school algebra, this text enables a solid understanding of the statistical concepts required to critically examine medical literature, scientifically plan and carry out medical investigations, and meaningfully analyze data.

Biostatistics and Computer-based Analysis of Health Data Using SAS

Biostatistics and Computer-based Analysis of Health Data Using SAS
Author: Christophe Lalanne
Publisher: Elsevier
Total Pages: 176
Release: 2017-06-22
Genre: Mathematics
ISBN: 0081011717
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This volume of the Biostatistics and Health Sciences Set focuses on statistics applied to clinical research.The use of SAS for data management and statistical modeling is illustrated using various examples. Many aspects of data processing and statistical analysis of cross-sectional and experimental medical data are covered, including regression models commonly found in medical statistics. This practical book is primarily intended for health researchers with a basic knowledge of statistical methodology. Assuming basic concepts, the authors focus on the practice of biostatistical methods essential to clinical research, epidemiology and analysis of biomedical data (including comparison of two groups, analysis of categorical data, ANOVA, linear and logistic regression, and survival analysis). The use of examples from clinical trials and epidemiological studies provide the basis for a series of practical exercises, which provide instruction and familiarize the reader with essential SAS commands. Presents the use of SAS software in the statistical approach for the management of data modeling Includes elements of the language and descriptive statistics Supplies measures of association, comparison of means, and proportions for two or more samples Explores linear and logistic regression Provides survival data analysis

Teaching Biostatistics in Medicine and Allied Health Sciences

Teaching Biostatistics in Medicine and Allied Health Sciences
Author: Damian J. J. Farnell
Publisher: Springer Nature
Total Pages: 219
Release: 2023-06-16
Genre: Medical
ISBN: 3031260104
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This book discusses the theory and practice of teaching biostatistics to students in the life sciences, in particular medical and dental trainees and researchers, as well as its crucial importance to biomedical research and evidence-based health care. Specific tools and resources to biostatistics teaching (e.g., “R shiny”) are described, and how they can be used effectively to increase interaction with students and improve engagement with the subject. The book is structured into three parts: teaching and learning of statistics in medicine and allied health sciences; the move to online learning and online learning methods, especially in light of the impact of COVID-19; and computer tools and resources. It provides a unique insight into teaching biostatistics to medical and dental students from some of the most prominent biostatisticians who also have a very strong interest in biostatistics pedagogy. Biostatistics teaching is important for maintaining the quality of biomedical research and also in evidence-based medicine, both of which are key to the health and well-being of the world population. This book is particularly useful to readers who are new to the field of biostatistics teaching as well as to more experienced teachers as it presents the latest accounts of the teaching and learning of biostatistics, recent experiences of increased use of online teaching, and useful computer resources and tools for teaching biostatistics.