Biostatistics 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 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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  • Author : Christophe Lalanne
  • Publisher : Elsevier
  • Pages : 206 pages
  • ISBN : 008101175X
  • Rating : 4/5 from 21 reviews
CLICK HERE TO GET THIS BOOKBiostatistics and Computer based Analysis of Health Data using R

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 : 13 July 2016
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 : 22 June 2017
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 : 06 September 2016
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

Analysis in Nutrition Research

Analysis in Nutrition Research
  • Author : George Pounis
  • Publisher : Academic Press
  • Release : 19 October 2018
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

Statistical Analysis of Questionnaires

Statistical Analysis of Questionnaires
  • Author : Francesco Bartolucci,Silvia Bacci,Michela Gnaldi
  • Publisher : CRC Press
  • Release : 23 July 2015
GET THIS BOOKStatistical Analysis of Questionnaires

Statistical Analysis of Questionnaires: A Unified Approach Based on R and Stata presents special statistical methods for analyzing data collected by questionnaires. The book takes an applied approach to testing and measurement tasks, mirroring the growing use of statistical methods and software in education, psychology, sociology, and other fields.

Analysis of Correlated Data with SAS and R

Analysis of Correlated Data with SAS and R
  • Author : Mohamed M. Shoukri
  • Publisher : CRC Press
  • Release : 27 April 2018
GET THIS BOOKAnalysis of Correlated Data with SAS and R

Analysis of Correlated Data with SAS and R: 4th edition presents an applied treatment of recently developed statistical models and methods for the analysis of hierarchical binary, count and continuous response data. It explains how to use procedures in SAS and packages in R for exploring data, fitting appropriate models, presenting programming codes and results. The book is designed for senior undergraduate and graduate students in the health sciences, epidemiology, statistics, and biostatistics as well as clinical researchers, and consulting

R for Health Data Science

R for Health Data Science
  • Author : Ewen Harrison,Riinu Pius
  • Publisher : CRC Press
  • Release : 31 December 2020
GET THIS BOOKR for Health Data Science

In this age of information, the manipulation, analysis, and interpretation of data have become a fundamental part of professional life; nowhere more so than in the delivery of healthcare. From the understanding of disease and the development of new treatments, to the diagnosis and management of individual patients, the use of data and technology is now an integral part of the business of healthcare. Those working in healthcare interact daily with data, often without realising it. The conversion of this

Analyzing Health Data in R for SAS Users

Analyzing Health Data in R for SAS Users
  • Author : Monika Maya Wahi,Peter Seebach
  • Publisher : CRC Press
  • Release : 22 November 2017
GET THIS BOOKAnalyzing Health Data in R for SAS Users

Analyzing Health Data in R for SAS Users is aimed at helping health data analysts who use SAS accomplish some of the same tasks in R. It is targeted to public health students and professionals who have a background in biostatistics and SAS software, but are new to R. For professors, it is useful as a textbook for a descriptive or regression modeling class, as it uses a publicly-available dataset for examples, and provides exercises at the end of each

Biostatistics for Epidemiology and Public Health Using R

Biostatistics for Epidemiology and Public Health Using R
  • Author : Bertram K.C. Chan, PhD
  • Publisher : Springer Publishing Company
  • Release : 05 November 2015
GET THIS BOOKBiostatistics for Epidemiology and Public Health Using R

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. 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-by-step approach to building skills. The text encompasses biostatistics from basic descriptive and quantitative statistics to survival analysis

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 : 19 November 2013
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

Analysis of Questionnaire Data with R

Analysis of Questionnaire Data with R
  • Author : Bruno Falissard
  • Publisher : CRC Press
  • Release : 21 September 2011
GET THIS BOOKAnalysis of Questionnaire Data with R

While theoretical statistics relies primarily on mathematics and hypothetical situations, statistical practice is a translation of a question formulated by a researcher into a series of variables linked by a statistical tool. As with written material, there are almost always differences between the meaning of the original text and translated text. Additionally, many versions can be suggested, each with their advantages and disadvantages. Analysis of Questionnaire Data with R translates certain classic research questions into statistical formulations. As indicated in

Clinical Trial Data Analysis Using R and SAS

Clinical Trial Data Analysis Using R and SAS
  • Author : Ding-Geng (Din) Chen,Karl E. Peace,Pinggao Zhang
  • Publisher : CRC Press
  • Release : 01 June 2017
GET THIS BOOKClinical Trial Data Analysis Using R and SAS

Review of the First Edition "The goal of this book, as stated by the authors, is to fill the knowledge gap that exists between developed statistical methods and the applications of these methods. Overall, this book achieves the goal successfully and does a nice job. I would highly recommend it ...The example-based approach is easy to follow and makes the book a very helpful desktop reference for many biostatistics methods."—Journal of Statistical Software Clinical Trial Data Analysis Using R

Statistical Analysis of Microbiome Data with R

Statistical Analysis of Microbiome Data with R
  • Author : Yinglin Xia,Jun Sun,Ding-Geng Chen
  • Publisher : Springer
  • Release : 06 October 2018
GET THIS BOOKStatistical Analysis of Microbiome Data with R

This unique book addresses the statistical modelling and analysis of microbiome data using cutting-edge R software. It includes real-world data from the authors’ research and from the public domain, and discusses the implementation of R for data analysis step by step. The data and R computer programs are publicly available, allowing readers to replicate the model development and data analysis presented in each chapter, so that these new methods can be readily applied in their own research. The book also

Biostatistics with R

Biostatistics with R
  • Author : Babak Shahbaba
  • Publisher : Springer Science & Business Media
  • Release : 15 December 2011
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