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Analysis Of Epidemiologic Data Using R


Analysis Of Epidemiologic Data Using R
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Analysis Of Epidemiologic Data Using R


Analysis Of Epidemiologic Data Using R
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Author : Robert Hirsch
language : en
Publisher: Springer Nature
Release Date : 2023-09-10

Analysis Of Epidemiologic Data Using R written by Robert Hirsch and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-10 with Science categories.


This book addresses the description and analysis of occurrence data frequently encountered in epidemiological studies. With the occurrence of Covid-19, people have been exposed to the analysis and interpretation of epidemiological data. To be informed consumers of this information, people need to understand the nature and analysis of these data. Effort is made to emphasize concepts rather than mathematics. Subjects range from description of the frequencies of disease to the analysis of associations between the occurrence of disease and exposure. Those analyses begin with simple associations and work up to complex relationships that involve the control of extraneous characteristics. Analyses rely on the statistical software R, which is freeware in wide use by professional epidemiologists and other scientists.



Analysis Of Epidemiological Data Using R And Epicalc


Analysis Of Epidemiological Data Using R And Epicalc
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Author : Virasakdi Chongsuvivatwong
language : en
Publisher:
Release Date : 2008

Analysis Of Epidemiological Data Using R And Epicalc written by Virasakdi Chongsuvivatwong and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with categories.




Biostatistics For Epidemiology And Public Health Using R


Biostatistics For Epidemiology And Public Health Using R
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Author : Bertram K.C. Chan, PhD
language : en
Publisher: Springer Publishing Company
Release Date : 2015-11-05

Biostatistics For Epidemiology And Public Health Using R written by Bertram K.C. Chan, PhD and has been published by Springer Publishing Company this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-11-05 with Medical categories.


Since it first appeared in 1996, the open-source programming language R has become increasingly popular as an environment for statistical analysis and graphical output. In addition to being freely available, R offers several advantages for biostatistics, including strong graphics capabilities, the ability to write customized functions, and its extensibility. This is the first textbook to present classical biostatistical analysis for epidemiology and related public health sciences to students using the R language. Based on the assumption that readers have minimal familiarity with statistical concepts, the author uses a step-bystep approach to building skills. The text encompasses biostatistics from basic descriptive and quantitative statistics to survival analysis and missing data analysis in epidemiology. Illustrative examples, including real-life research problems and exercises drawn from such areas as nutrition, environmental health, and behavioral health, engage students and reinforce the understanding of R. These examples illustrate the replication of R for biostatistical calculations and graphical display of results. The text covers both essential and advanced techniques and applications in biostatistics that are relevant to epidemiology. This text is supplemented with teaching resources, including an online guide for students in solving exercises and an instructor's manual. KEY FEATURES: First overview biostatistics textbook for epidemiology and public health that uses the open-source R program Covers essential and advanced techniques and applications in biostatistics as relevant to epidemiology Features abundant examples and exercises to illustrate the application of R language for biostatistical calculations and graphical displays of results Includes online student solutions guide and instructor's manual



Applied Epidemiology Using R And Rstudio


Applied Epidemiology Using R And Rstudio
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Author : Tomas J. Aragon
language : en
Publisher: Chapman and Hall/CRC
Release Date : 2014-12-15

Applied Epidemiology Using R And Rstudio written by Tomas J. Aragon and has been published by Chapman and Hall/CRC this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-12-15 with Mathematics categories.


This book fills the gap as an introduction to R specifically for epidemiologists. It presents all the necessary background to get started with R, work with R data objects, and manage epidemiological data in R. It then covers data analysis and graphics for addressing problems in epidemiology, including the key topics of confounding and outbreak analysis. The text is packed with exercises to enhance understanding and detailed worked examples using real data from epidemiological studies.



Statistical Analysis Of Epidemiologic Data


Statistical Analysis Of Epidemiologic Data
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Author : Steve Selvin
language : en
Publisher: Oxford University Press
Release Date : 2004-05-13

Statistical Analysis Of Epidemiologic Data written by Steve Selvin 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 2004-05-13 with Medical categories.


Analytic procedures suitable for the study of human disease are scattered throughout the statistical and epidemiologic literature. Explanations of their properties are frequently presented in mathematical and theoretical language. This well-established text gives readers a clear understanding of the statistical methods that are widely used in epidemiologic research without depending on advanced mathematical or statistical theory. By applying these methods to actual data, Selvin reveals the strengths and weaknesses of each analytic approach. He combines techniques from the fields of statistics, biostatistics, demography and epidemiology to present a comprehensive overview that does not require computational details of the statistical techniques described. For the Third Edition, Selvin took out some old material (e.g. the section on rarely used cross-over designs) and added new material (e.g. sections on frequently used contingency table analysis). Throughout the text he enriched existing discussions with new elements, including the analysis of multi-level categorical data and simple, intuitive arguments that exponential survival times cause the hazard function to be constant. He added a dozen new applied examples to illustrate such topics as the pitfalls of proportional mortality data, the analysis of matched pair categorical data, and the age-adjustment of mortality rates based on statistical models. The most important new feature is a chapter on Poisson regression analysis. This essential statistical tool permits the multivariable analysis of rates, probabilities and counts.



Clinical Trial Data Analysis Using R


Clinical Trial Data Analysis Using R
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Author : Ding-Geng (Din) Chen
language : en
Publisher: CRC Press
Release Date : 2010-12-14

Clinical Trial Data Analysis Using R written by Ding-Geng (Din) Chen and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-12-14 with Mathematics categories.


Too often in biostatistical research and clinical trials, a knowledge gap exists between developed statistical methods and the applications of these methods. Filling this gap, Clinical Trial Data Analysis Using R provides a thorough presentation of biostatistical analyses of clinical trial data and shows step by step how to implement the statistical methods using R. The book’s practical, detailed approach draws on the authors’ 30 years of real-world experience in biostatistical research and clinical development. Each chapter presents examples of clinical trials based on the authors’ actual experiences in clinical drug development. Various biostatistical methods for analyzing the data are then identified. The authors develop analysis code step by step using appropriate R packages and functions. This approach enables readers to gain an understanding of the analysis methods and R implementation so that they can use R to analyze their own clinical trial data. With step-by-step illustrations of R implementations, this book shows how to easily use R to simulate and analyze data from a clinical trial. It describes numerous up-to-date statistical methods and offers sound guidance on the processes involved in clinical trials.



Data Science For Infectious Disease Data Analytics


Data Science For Infectious Disease Data Analytics
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Author : Lily Wang
language : en
Publisher: CRC Press
Release Date : 2022-12-05

Data Science For Infectious Disease Data Analytics written by Lily Wang and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-05 with Business & Economics categories.


Data Science for Infectious Disease Data Analytics: An Introduction with R provides an overview of modern data science tools and methods that have been developed specifically to analyze infectious disease data. With a quick start guide to epidemiological data visualization and analysis in R, this book spans the gulf between academia and practices providing many lively, instructive data analysis examples using the most up-to-date data, such as the newly discovered coronavirus disease (COVID-19). The primary emphasis of this book is the data science procedures in epidemiological studies, including data wrangling, visualization, interpretation, predictive modeling, and inference, which is of immense importance due to increasingly diverse and nonexperimental data across a wide range of fields. The knowledge and skills readers gain from this book are also transferable to other areas, such as public health, business analytics, environmental studies, or spatio-temporal data visualization and analysis in general. Aimed at readers with an undergraduate knowledge of mathematics and statistics, this book is an ideal introduction to the development and implementation of data science in epidemiology. Features Describes the entire data science procedure of how the infectious disease data are collected, curated, visualized, and fed to predictive models, which facilitates effective communication between data sources, scientists, and decision-makers. Explains practical concepts of infectious disease data and provides particular data science perspectives. Overview of the unique features and issues of infectious disease data and how they impact epidemic modeling and projection. Introduces various classes of models and state-of-the-art learning methods to analyze infectious diseases data with valuable insights on how different models and methods could be connected.



Epidemics


Epidemics
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Author : Ottar N. Bjørnstad
language : en
Publisher: Springer
Release Date : 2018-10-30

Epidemics written by Ottar N. Bjørnstad and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-30 with Medical categories.


This book is designed to be a practical study in infectious disease dynamics. The book offers an easy to follow implementation and analysis of mathematical epidemiology. The book focuses on recent case studies in order to explore various conceptual, mathematical, and statistical issues. The dynamics of infectious diseases shows a wide diversity of pattern. Some have locally persistent chains-of-transmission, others persist spatially in ‘consumer-resource metapopulations’. Some infections are prevalent among the young, some among the old and some are age-invariant. Temporally, some diseases have little variation in prevalence, some have predictable seasonal shifts and others exhibit violent epidemics that may be regular or irregular in their timing. Models and ‘models-with-data’ have proved invaluable for understanding and predicting this diversity, and thence help improve intervention and control. Using mathematical models to understand infectious disease dynamics has a very rich history in epidemiology. The field has seen broad expansions of theories as well as a surge in real-life application of mathematics to dynamics and control of infectious disease. The chapters of Epidemics: Models and Data using R have been organized in a reasonably logical way: Chapters 1-10 is a mix and match of models, data and statistics pertaining to local disease dynamics; Chapters 11-13 pertains to spatial and spatiotemporal dynamics; Chapter 14 highlights similarities between the dynamics of infectious disease and parasitoid-host dynamics; Finally, Chapters 15 and 16 overview additional statistical methodology useful in studies of infectious disease dynamics. This book can be used as a guide for working with data, models and ‘models-and-data’ to understand epidemics and infectious disease dynamics in space and time.



Spatio Temporal Methods In Environmental Epidemiology With R


Spatio Temporal Methods In Environmental Epidemiology With R
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Author : Gavin Shaddick
language : en
Publisher: CRC Press
Release Date : 2023-12-12

Spatio Temporal Methods In Environmental Epidemiology With R written by Gavin Shaddick and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-12 with Medical categories.


Spatio-Temporal Methods in Environmental Epidemiology with R, like its First Edition, explores the interface between environmental epidemiology and spatio-temporal modeling. It links recent developments in spatio-temporal theory with epidemiological applications. Drawing on real-life problems, it shows how recent advances in methodology can assess the health risks associated with environmental hazards. The book's clear guidelines enable the implementation of the methodology and estimation of risks in practice. New additions to the Second Edition include: a thorough exploration of the underlying concepts behind knowledge discovery through data; a new chapter on extracting information from data using R and the tidyverse; additional material on methods for Bayesian computation, including the use of NIMBLE and Stan; new methods for performing spatio-temporal analysis and an updated chapter containing further topics. Throughout the book there are new examples, and the presentation of R code for examples has been extended. Along with these additions, the book now has a GitHub site (https://spacetime-environ.github.io/stepi2) that contains data, code and further worked examples. Features: • Explores the interface between environmental epidemiology and spatio­-temporal modeling • Incorporates examples that show how spatio-temporal methodology can inform societal concerns about the effects of environmental hazards on health • Uses a Bayesian foundation on which to build an integrated approach to spatio-temporal modeling and environmental epidemiology • Discusses data analysis and topics such as data visualization, mapping, wrangling and analysis • Shows how to design networks for monitoring hazardous environmental processes and the ill effects of preferential sampling • Through the listing and application of code, shows the power of R, tidyverse, NIMBLE and Stan and other modern tools in performing complex data analysis and modeling Representing a continuing important direction in environmental epidemiology, this book – in full color throughout – underscores the increasing need to consider dependencies in both space and time when modeling epidemiological data. Readers will learn how to identify and model patterns in spatio-temporal data and how to exploit dependencies over space and time to reduce bias and inefficiency when estimating risks to health.



Statistical Methods For Environmental Epidemiology With R


Statistical Methods For Environmental Epidemiology With R
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Author : Roger D. Peng
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-12-15

Statistical Methods For Environmental Epidemiology With R written by Roger D. Peng and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-12-15 with Medical categories.


As an area of statistical application, environmental epidemiology and more speci cally, the estimation of health risk associated with the exposure to - vironmental agents, has led to the development of several statistical methods and software that can then be applied to other scienti c areas. The stat- tical analyses aimed at addressing questions in environmental epidemiology have the following characteristics. Often the signal-to-noise ratio in the data is low and the targets of inference are inherently small risks. These constraints typically lead to the development and use of more sophisticated (and pot- tially less transparent) statistical models and the integration of large hi- dimensional databases. New technologies and the widespread availability of powerful computing are also adding to the complexities of scienti c inves- gation by allowing researchers to t large numbers of models and search over many sets of variables. As the number of variables measured increases, so do the degrees of freedom for in uencing the association between a risk factor and an outcome of interest. We have written this book, in part, to describe our experiences developing and applying statistical methods for the estimation for air pollution health e ects. Our experience has convinced us that the application of modern s- tistical methodology in a reproducible manner can bring to bear subst- tial bene ts to policy-makers and scientists in this area. We believe that the methods described in this book are applicable to other areas of environmental epidemiology, particularly those areas involving spatial{temporal exposures.