Biostatistics and Computer based Analysis of Health Data using R

Book Biostatistics and Computer based Analysis of Health Data using R Cover

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  • Publisher : Elsevier
  • Release : 13 July 2016
  • ISBN : 9780081011751
  • Page : 206 pages
  • Rating : 4.5/5 from 103 voters

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Biostatistics and Computer-Based Analysis of Health Data Using the R Software addresses the concept that many of the actions performed by statistical software comes back to the handling, manipulation, or even transformation of digital data. It is therefore of primary importance to understand how statistical data is displayed and how it can be exploited by software such as R. In this book, the authors explore basic and variable commands, sample comparisons, analysis of variance, epidemiological studies, and censored data. With proposed applications and examples of commands following each chapter, this book allows readers to apply advanced statistical concepts to their own data and software. Features useful commands for describing a data table composed made up of quantitative and qualitative variables Includes measures of association encountered in epidemiological studies, odds ratio, relative risk, and prevalence Presents an analysis of censored data, the key main tests associated with the construction of a survival curve (log-rank test or Wilcoxon), and the Cox regression model

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Biostatistics and Computer-based Analysis of Health Data using R

Biostatistics and Computer-based Analysis of Health Data using R
  • Author : Christophe Lalanne,Mounir Mesbah
  • Publisher : Elsevier
  • Release Date : 2016-07-13
  • ISBN : 9780081011751
GET THIS BOOKBiostatistics and Computer-based Analysis of Health Data using R

Biostatistics and Computer-Based Analysis of Health Data Using the R Software addresses the concept that many of the actions performed by statistical software comes back to the handling, manipulation, or even transformation of digital data. It is therefore of primary importance to understand how statistical data is displayed and how it can be exploited by software such as R. In this book, the authors explore basic and variable commands, sample comparisons, analysis of variance, epidemiological studies, and censored data. With

Biostatistics and Computer-based Analysis of Health Data Using SAS

Biostatistics and Computer-based Analysis of Health Data Using SAS
  • Author : Christophe Lalanne,Mounir Mesbah
  • Publisher : Elsevier
  • Release Date : 2017-06-22
  • ISBN : 9780081011713
GET THIS BOOKBiostatistics and Computer-based Analysis of Health Data Using SAS

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

Biostatistics and Computer-based Analysis of Health Data using Stata

Biostatistics and Computer-based Analysis of Health Data using Stata
  • Author : Christophe Lalanne,Mounir Mesbah
  • Publisher : Elsevier
  • Release Date : 2016-09-06
  • ISBN : 9780081010846
GET THIS BOOKBiostatistics and Computer-based Analysis of Health Data using Stata

This volume of the Biostatistics and Health Sciences Set focuses on statistics applied to clinical research. The use of Stata 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 basic knowledge of statistical methodology. Assuming basic concepts, the authors focus on the practice of

Biostatistics and Computer-Based Analysis of Health Data Using the R Software

Biostatistics and Computer-Based Analysis of Health Data Using the R Software
  • Author : Mounir Mesbah,Christophe Lalanne
  • Publisher : Iste Press - Elsevier
  • Release Date : 2016-03-15
  • ISBN : 178548088X
GET THIS BOOKBiostatistics and Computer-Based Analysis of Health Data Using the R Software

" Biostatistics and Computer-Based Analysis of Health Data Using the R Software" addresses the concept that many of the actions performed by statistical software comes back to the handling, manipulation, or even transformation of digital data. It is therefore of primary importance to understand how statistical data is displayed and how it can be exploited by software such as R. In this book, the authors explore basic and variable commands, sample comparisons, analysis of variance, epidemiological studies, and censored data. With

Analysis in Nutrition Research

Analysis in Nutrition Research
  • Author : George Pounis
  • Publisher : Academic Press
  • Release Date : 2018-10-19
  • ISBN : 9780128145579
GET THIS BOOKAnalysis in Nutrition Research

Analysis in Nutrition Research: Principles of Statistical Methodology and Interpretation of the Results describes, in a comprehensive manner, the methodologies of quantitative analysis of data originating specifically from nutrition studies. The book summarizes various study designs in nutrition research, research hypotheses, the proper management of dietary data, and analytical methodologies, with a specific focus on how to interpret the results of any given study. In addition, it provides a comprehensive overview of the methodologies used in study design and the

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  • Author : Christo El Morr,Manar Jammal,Hossam Ali-Hassan,Walid EI-Hallak
  • Publisher : Springer Nature
  • Release Date : 2022-11-29
  • ISBN : 9783031169908
GET THIS BOOKMachine Learning for Practical Decision Making

This book provides a hands-on introduction to Machine Learning (ML) from a multidisciplinary perspective that does not require a background in data science or computer science. It explains ML using simple language and a straightforward approach guided by real-world examples in areas such as health informatics, information technology, and business analytics. The book will help readers understand the various key algorithms, major software tools, and their applications. Moreover, through examples from the healthcare and business analytics fields, it demonstrates how

Introduction to Data Analysis and Graphical Presentation in Biostatistics with R

Introduction to Data Analysis and Graphical Presentation in Biostatistics with R
  • Author : Thomas W. MacFarland
  • Publisher : Springer
  • Release Date : 2013-11-29
  • ISBN : 3319025317
GET THIS BOOKIntroduction to Data Analysis and Graphical Presentation in Biostatistics with R

Through real-world datasets, this book shows the reader how to work with material in biostatistics using the open source software R. These include tools that are critical to dealing with missing data, which is a pressing scientific issue for those engaged in biostatistics. Readers will be equipped to run analyses and make graphical presentations based on the sample dataset and their own data. The hands-on approach will benefit students and ensure the accessibility of this book for readers with a

Introduction to Data Analysis and Graphical Presentation in Biostatistics with R

Introduction to Data Analysis and Graphical Presentation in Biostatistics with R
  • Author : Thomas W. MacFarland
  • Publisher : Springer Science & Business Media
  • Release Date : 2013-11-19
  • ISBN : 9783319025322
GET THIS BOOKIntroduction to Data Analysis and Graphical Presentation in Biostatistics with R

Through real-world datasets, this book shows the reader how to work with material in biostatistics using the open source software R. These include tools that are critical to dealing with missing data, which is a pressing scientific issue for those engaged in biostatistics. Readers will be equipped to run analyses and make graphical presentations based on the sample dataset and their own data. The hands-on approach will benefit students and ensure the accessibility of this book for readers with a

Using R and RStudio for Data Management, Statistical Analysis, and Graphics

Using R and RStudio for Data Management, Statistical Analysis, and Graphics
  • Author : Nicholas J. Horton,Ken Kleinman
  • Publisher : CRC Press
  • Release Date : 2015-03-10
  • ISBN : 9781482237375
GET THIS BOOKUsing R and RStudio for Data Management, Statistical Analysis, and Graphics

Improve Your Analytical SkillsIncorporating the latest R packages as well as new case studies and applications, Using R and RStudio for Data Management, Statistical Analysis, and Graphics, Second Edition covers the aspects of R most often used by statistical analysts. New users of R will find the book's simple approach easy to understand while more

Biostatistics with R

Biostatistics with R
  • Author : Babak Shahbaba
  • Publisher : Springer Science & Business Media
  • Release Date : 2011-12-15
  • ISBN : 9781461413028
GET THIS BOOKBiostatistics with R

Biostatistics with R is designed around the dynamic interplay among statistical methods, their applications in biology, and their implementation. The book explains basic statistical concepts with a simple yet rigorous language. The development of ideas is in the context of real applied problems, for which step-by-step instructions for using R and R-Commander are provided. Topics include data exploration, estimation, hypothesis testing, linear regression analysis, and clustering with two appendices on installing and using R and R-Commander. A novel feature of

Using R for Introductory Statistics

Using R for Introductory Statistics
  • Author : John Verzani
  • Publisher : CRC Press
  • Release Date : 2018-10-03
  • ISBN : 9781315362670
GET THIS BOOKUsing R for Introductory Statistics

The second edition of a bestselling textbook, Using R for Introductory Statistics guides students through the basics of R, helping them overcome the sometimes steep learning curve. The author does this by breaking the material down into small, task-oriented steps. The second edition maintains the features that made the first edition so popular, while updating data, examples, and changes to R in line with the current version. See What’s New in the Second Edition: Increased emphasis on more idiomatic

Biomedical Index to PHS-supported Research

Biomedical Index to PHS-supported Research
  • Author : Anonim
  • Publisher : Unknown
  • Release Date : 1988
  • ISBN : STANFORD:36105119624679
GET THIS BOOKBiomedical Index to PHS-supported Research

Research Awards Index

Research Awards Index
  • Author : Anonim
  • Publisher : Unknown
  • Release Date : 1989
  • ISBN : UOM:39015014022589
GET THIS BOOKResearch Awards Index

Computer-assisted Analysis of Mixtures and Applications

Computer-assisted Analysis of Mixtures and Applications
  • Author : Dankmar Böhning
  • Publisher : CRC Press
  • Release Date : 1999
  • ISBN : 0849303850
GET THIS BOOKComputer-assisted Analysis of Mixtures and Applications

Review recent developments in the area of computer assisted analysis of mixture distributions. Beside developments in theory & algorithms, Computer Assisted Analysis of Mixtures focuses on developments in biometric applications, such as meta-analysis, disease mapping, fertility studies, estimation of prevalence under clustering, & estimation of the distribution of survival time under interval-censoring. The approach is nonparametric for the mixing distribution, including leaving the number of components of the mixing distribution unknown.

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Big Data in Multimodal Medical Imaging
  • Author : Ayman El-Baz,Jasjit S. Suri
  • Publisher : CRC Press
  • Release Date : 2019-11-05
  • ISBN : 9781351380737
GET THIS BOOKBig Data in Multimodal Medical Imaging

There is an urgent need to develop and integrate new statistical, mathematical, visualization, and computational models with the ability to analyze Big Data in order to retrieve useful information to aid clinicians in accurately diagnosing and treating patients. The main focus of this book is to review and summarize state-of-the-art big data and deep learning approaches to analyze and integrate multiple data types for the creation of a decision matrix to aid clinicians in the early diagnosis and identification of