Analysis Of Epidemiological Data Using R And Epicalc

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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.

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.

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

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.

Statistical Methods For Hospital Monitoring With R

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Author : Anthony Morton
language : en
Publisher: John Wiley & Sons
Release Date : 2013-06-27

Statistical Methods For Hospital Monitoring With R written by Anthony Morton and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-27 with Medical categories.

Hospitals monitoring is becoming more complex and is increasing both because staff want their data analysed and because of increasing mandated surveillance. This book provides a suite of functions in R, enabling scientists and data analysts working in infection management and quality improvement departments in hospitals, to analyse their often non-independent data which is frequently in the form of trended, over-dispersed and sometimes auto-correlated time series; this is often difficult to analyse using standard office software. This book provides much-needed guidance on data analysis using R for the growing number of scientists in hospital departments who are responsible for producing reports, and who may have limited statistical expertise. This book explores data analysis using R and is aimed at scientists in hospital departments who are responsible for producing reports, and who are involved in improving safety. Professionals working in the healthcare quality and safety community will also find this book of interest Statistical Methods for Hospital Monitoring with R: Provides functions to perform quality improvement and infection management data analysis. Explores the characteristics of complex systems, such as self-organisation and emergent behaviour, along with their implications for such activities as root-cause analysis and the Pareto principle that seek few key causes of adverse events. Provides a summary of key non-statistical aspects of hospital safety and easy to use functions. Provides R scripts in an accompanying web site enabling analyses to be performed by the reader http://www.wiley.com/go/hospital_monitoring Covers issues that will be of increasing importance in the future, such as, generalised additive models, and complex systems, networks and power laws.

Biostatistics For Human Genetic Epidemiology

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Author : Bertram K. C. Chan
language : en
Publisher: Springer
Release Date : 2018-10-24

Biostatistics For Human Genetic Epidemiology written by Bertram K. C. Chan and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-24 with Medical categories.

The book illustrates how biostatistics may numerically summarize human genetic epidemiology using R, and may be used successfully to solve problems in quantitative Genetic Epidemiology Biostatistics for Human Genetic Epidemiology provides statistical methodologies and R recipes for human genetic epidemiologic problems. It begins by introducing all the necessary probabilistic and statistical foundations, before moving on to topics related human genetic epidemiology, with R codes illustrations for various examples. This clear and concise book covers human genetic epidemiology, using R in data analysis, including multivariate data analysis. It examines probabilistic and statistical theories for modeling human genetic epidemiology – leading the readers through an effective epidemiologic model, from simple to advanced levels. Classical mathematical, probabilistic, and statistical theory are thoroughly discussed and presented. This book also presents R as a calculator and using R in data analysis. Additionally, it covers Advanced Human Genetic Data Concepts, the Study of Human Genetic Variation, Manhattan Plots, as well as the Procedures for Multiple Comparison. Numerous Worked Examples are provided for illustrations of concepts and real-life applications. Biostatistics for Human Genetic Epidemiology is an ideal reference for professionals and students in Medicine (particularly in Preventive Medicine and Public Health Medical Practices), as well as in Genetics, Epidemiology, and Biostatistics.

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.

Teaching Epidemiology

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Author : Jørn Olsen
language : en
Publisher: Oxford University Press, USA
Release Date : 2010-04-15

Teaching Epidemiology written by Jørn Olsen and has been published by Oxford University Press, USA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-04-15 with Medical categories.

Teaching Epidemiology is published in collaboration with the International Association of Epidemiology (IEA) and the European Educational Programme in Epidemiology (EEPE) --Book Jacket.

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

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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.