Biostatistics 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 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

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  • Author : Christophe Lalanne
  • Publisher : Elsevier
  • Pages : 174 pages
  • ISBN : 0081011717
  • Rating : 4/5 from 21 reviews
CLICK HERE TO GET THIS BOOKBiostatistics and Computer based Analysis of Health Data Using SAS

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

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

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

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

Statistical Analysis of Medical Data Using SAS

Statistical Analysis of Medical Data Using SAS
  • Author : Geoff Der,Brian S. Everitt
  • Publisher : CRC Press
  • Release : 20 September 2005
GET THIS BOOKStatistical Analysis of Medical Data Using SAS

Statistical analysis is ubiquitous in modern medical research. Logistic regression, generalized linear models, random effects models, and Cox's regression all have become commonplace in the medical literature. But while statistical software such as SAS make routine application of these techniques possible, users who are not primarily statisticians must take care to correctly implement the various procedures and correctly interpret the output. Statistical Analysis of Medical Data Using SAS demonstrates how to use SAS to analyze medical data. Each chapter addresses

Applied Medical Statistics Using SAS

Applied Medical Statistics Using SAS
  • Author : Geoff Der,Brian S. Everitt
  • Publisher : CRC Press
  • Release : 01 October 2012
GET THIS BOOKApplied Medical Statistics Using SAS

Written with medical statisticians and medical researchers in mind, this intermediate-level reference explores the use of SAS for analyzing medical data. Applied Medical Statistics Using SAS covers the whole range of modern statistical methods used in the analysis of medical data, including regression, analysis of variance and covariance, longitudi

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

Using SAS for Data Management, Statistical Analysis, and Graphics

Using SAS for Data Management, Statistical Analysis, and Graphics
  • Author : Ken Kleinman,Nicholas J. Horton
  • Publisher : CRC Press
  • Release : 28 July 2010
GET THIS BOOKUsing SAS for Data Management, Statistical Analysis, and Graphics

Quick and Easy Access to Key Elements of Documentation Includes worked examples across a wide variety of applications, tasks, and graphics A unique companion for statistical coders, Using SAS for Data Management, Statistical Analysis, and Graphics presents an easy way to learn how to perform an analytical task in SAS, without having to navigate through the extensive, idiosyncratic, and sometimes unwieldy software documentation. Organized by short, clear descriptive entries, the book covers many common tasks, such as data management, descriptive

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

Analysis of Clinical Trials Using SAS

Analysis of Clinical Trials Using SAS
  • Author : Alex Dmitrienko,Geert Molenberghs,Christy Chuang-Stein,Walter W. Offen
  • Publisher : SAS Institute
  • Release : 18 February 2005
GET THIS BOOKAnalysis of Clinical Trials Using SAS

In Analysis of Clinical Trials Using SAS: A Practical Guide, Alex Dmitrienko, Geert Molenberghs, Christy Chuang-Stein, and Walter Offen bridge the gap between modern statistical methodology and real-world clinical trial applications. Step-by-step instructions illustrated with examples from actual trials and case studies serve to define a statistical method and its relevance in a clinical trials setting and to illustrate how to implement the method rapidly and efficiently using the power of SAS software. Topics reflect the International Conference on Harmonization (

A Handbook of Statistical Graphics Using SAS ODS

A Handbook of Statistical Graphics Using SAS ODS
  • Author : Geoff Der,Brian S. Everitt
  • Publisher : CRC Press
  • Release : 15 August 2014
GET THIS BOOKA Handbook of Statistical Graphics Using SAS ODS

Easily Use SAS to Produce Your Graphics Diagrams, plots, and other types of graphics are indispensable components in nearly all phases of statistical analysis, from the initial assessment of the data to the selection of appropriate statistical models to the diagnosis of the chosen models once they have been fitted to the data. Harnessing the full graphics capabilities of SAS, A Handbook of Statistical Graphics Using SAS ODS covers essential graphical methods needed in every statistician’s toolkit. It explains

Design and Analysis of Experiments with R

Design and Analysis of Experiments with R
  • Author : John Lawson
  • Publisher : CRC Press
  • Release : 17 December 2014
GET THIS BOOKDesign and Analysis of Experiments with R

Design and Analysis of Experiments with R presents a unified treatment of experimental designs and design concepts commonly used in practice. It connects the objectives of research to the type of experimental design required, describes the process of creating the design and collecting the data, shows how to perform the proper analysis of the data,

Analysis of Observational Health Care Data Using SAS

Analysis of Observational Health Care Data Using SAS
  • Author : Douglas E. Faries,Andrew C. Leon,Josep Maria Haro,Robert L. Obenchain
  • Publisher : SAS Press
  • Release : 01 January 2010
GET THIS BOOKAnalysis of Observational Health Care Data Using SAS

This book guides researchers in performing and presenting high-quality analyses of all kinds of non-randomized studies, including analyses of observational studies, claims database analyses, assessment of registry data, survey data, pharmaco-economic data, and many more applications. The text is sufficiently detailed to provide not only general guidance, but to help the researcher through all of the standard issues that arise in such analyses. Just enough theory is included to allow the reader to understand the pros and cons of alternative

SAS for Epidemiologists

SAS for Epidemiologists
  • Author : Charles DiMaggio
  • Publisher : Springer Science & Business Media
  • Release : 25 October 2012
GET THIS BOOKSAS for Epidemiologists

This comprehensive text covers the use of SAS for epidemiology and public health research. Developed with students in mind and from their feedback, the text addresses this material in a straightforward manner with a multitude of examples. It is directly applicable to students and researchers in the fields of public health, biostatistics and epidemiology. Through a “hands on” approach to the use of SAS for a broad number of epidemiologic analyses, readers learn techniques for data entry and cleaning, categorical