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
Publsiher: Elsevier
Total Pages: 206
Release: 2016-07-13
ISBN 10: 008101175X
ISBN 13: 9780081011751
Language: EN, FR, DE, ES & NL

Biostatistics and Computer based Analysis of Health Data using R Book Review:

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

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
Publsiher: Elsevier
Total Pages: 174
Release: 2017-06-22
ISBN 10: 0081011717
ISBN 13: 9780081011713
Language: EN, FR, DE, ES & NL

Biostatistics and Computer based Analysis of Health Data Using SAS Book Review:

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

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
Publsiher: Elsevier
Total Pages: 134
Release: 2016-09-06
ISBN 10: 0081010842
ISBN 13: 9780081010846
Language: EN, FR, DE, ES & NL

Biostatistics and Computer based Analysis of Health Data using Stata Book Review:

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 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 epideomological studies provide the basis for a series of practical exercises, which provide instruction and familiarize the reader with essential Stata packages and commands. Provides detailed examples of the use of Stata for common biostatistical tasks in medical research Features a work program structured around the four previous chapters and a series of practical exercises with commented corrections Includes an appendix to help the reader familiarize themselves with additional packages and commands Focuses on the practice of biostatistical methods that are essential to clinical research, epidemiology, and analysis of biomedical data

Analysis in Nutrition Research

Analysis in Nutrition Research
Author: George Pounis
Publsiher: Academic Press
Total Pages: 408
Release: 2018-10-19
ISBN 10: 0128145579
ISBN 13: 9780128145579
Language: EN, FR, DE, ES & NL

Analysis in Nutrition Research Book Review:

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 management and analysis of collected data, paying particular attention to all of the available, modern methodologies and techniques. Users will find an overview of the recent challenges and debates in the field of nutrition research that will define major research hypotheses for research in the next ten years. Nutrition scientists, researchers and undergraduate and postgraduate students will benefit from this thorough publication on the topic. Provides a comprehensive presentation of the various study designs applied in nutrition research Contains a parallel description of statistical methodologies used for each study design Presents data management methodologies used specifically in nutrition research Describes methodologies using both a theoretical and applied approach Illustrates modern techniques in dietary pattern analysis Summarizes current topics in the field of nutrition research that will define major research hypotheses for research in the next ten years

Using R for Biostatistics

Using R for Biostatistics
Author: Thomas W. MacFarland,Jan M. Yates
Publsiher: Springer Nature
Total Pages: 902
Release: 2021-03-02
ISBN 10: 3030624048
ISBN 13: 9783030624040
Language: EN, FR, DE, ES & NL

Using R for Biostatistics Book Review:

This book introduces the open source R software language that can be implemented in biostatistics for data organization, statistical analysis, and graphical presentation. In the years since the authors’ 2014 work Introduction to Data Analysis and Graphical Presentation in Biostatistics with R, the R user community has grown exponentially and the R language has increased in maturity and functionality. This updated volume expands upon skill-sets useful for students and practitioners in the biological sciences by describing how to work with data in an efficient manner, how to engage in meaningful statistical analyses from multiple perspectives, and how to generate high-quality graphics for professional publication of their research. A common theme for research in the diverse biological sciences is that decision-making depends on the empirical use of data. Beginning with a focus on data from a parametric perspective, the authors address topics such as Student t-Tests for independent samples and matched pairs; oneway and twoway analyses of variance; and correlation and linear regression. The authors also demonstrate the importance of a nonparametric perspective for quality assurance through chapters on the Mann-Whitney U Test, Wilcoxon Matched-Pairs Signed-Ranks test, Kruskal-Wallis H-Test for Oneway Analysis of Variance, and the Friedman Twoway Analysis of Variance. To address the element of data presentation, the book also provides an extensive review of the many graphical functions available with R. There are now perhaps more than 15,000 external packages available to the R community. The authors place special emphasis on graphics using the lattice package and the ggplot2 package, as well as less common, but equally useful, figures such as bean plots, strip charts, and violin plots. A robust package of supplementary material, as well as an introduction of the development of both R and the discipline of biostatistics, makes this ideal for novice learners as well as more experienced practitioners.

Biostatistics in Public Health Using STATA

Biostatistics in Public Health Using STATA
Author: Erick L. Suárez,Cynthia M. Pérez,Graciela M. Nogueras,Camille Moreno-Gorrín
Publsiher: CRC Press
Total Pages: 206
Release: 2016-03-24
ISBN 10: 1498722024
ISBN 13: 9781498722025
Language: EN, FR, DE, ES & NL

Biostatistics in Public Health Using STATA Book Review:

Striking a balance between theory, application, and programming, Biostatistics in Public Health Using STATA is a user-friendly guide to applied statistical analysis in public health using STATA version 14. The book supplies public health practitioners and students with the opportunity to gain expertise in the application of statistics in epidemiolo

R for Health Data Science

R for Health Data Science
Author: Ewen Harrison,Riinu Pius
Publsiher: CRC Press
Total Pages: 346
Release: 2020-12-31
ISBN 10: 1000226166
ISBN 13: 9781000226164
Language: EN, FR, DE, ES & NL

R for Health Data Science Book Review:

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 avalanche of information to useful knowledge is essential for high-quality patient care. R for Health Data Science includes everything a healthcare professional needs to go from R novice to R guru. By the end of this book, you will be taking a sophisticated approach to health data science with beautiful visualisations, elegant tables, and nuanced analyses. Features Provides an introduction to the fundamentals of R for healthcare professionals Highlights the most popular statistical approaches to health data science Written to be as accessible as possible with minimal mathematics Emphasises the importance of truly understanding the underlying data through the use of plots Includes numerous examples that can be adapted for your own data Helps you create publishable documents and collaborate across teams With this book, you are in safe hands – Prof. Harrison is a clinician and Dr. Pius is a data scientist, bringing 25 years’ combined experience of using R at the coal face. This content has been taught to hundreds of individuals from a variety of backgrounds, from rank beginners to experts moving to R from other platforms.

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
Publsiher: Springer Science & Business Media
Total Pages: 167
Release: 2013-11-19
ISBN 10: 3319025325
ISBN 13: 9783319025322
Language: EN, FR, DE, ES & NL

Introduction to Data Analysis and Graphical Presentation in Biostatistics with R Book Review:

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 basic understanding of R. Topics include: an introduction to Biostatistics and R, data exploration, descriptive statistics and measures of central tendency, t-Test for independent samples, t-Test for matched pairs, ANOVA, correlation and linear regression, and advice for future work.

Analyzing Health Data in R for SAS Users

Analyzing Health Data in R for SAS Users
Author: Monika Maya Wahi,Peter Seebach
Publsiher: CRC Press
Total Pages: 320
Release: 2017-11-22
ISBN 10: 1351394274
ISBN 13: 9781351394277
Language: EN, FR, DE, ES & NL

Analyzing Health Data in R for SAS Users Book Review:

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 chapter. For students and public health professionals, not only is it a gentle introduction to R, but it can serve as a guide to developing the results for a research report using R software. Features: Gives examples in both SAS and R Demonstrates descriptive statistics as well as linear and logistic regression Provides exercise questions and answers at the end of each chapter Uses examples from the publicly available dataset, Behavioral Risk Factor Surveillance System (BRFSS) 2014 data Guides the reader on producing a health analysis that could be published as a research report Gives an example of hypothesis-driven data analysis Provides examples of plots with a color insert

Biostatistics for Epidemiology and Public Health Using R

Biostatistics for Epidemiology and Public Health Using R
Author: Bertram K.C. Chan, PhD
Publsiher: Springer Publishing Company
Total Pages: 500
Release: 2015-11-05
ISBN 10: 0826110266
ISBN 13: 9780826110268
Language: EN, FR, DE, ES & NL

Biostatistics for Epidemiology and Public Health Using R Book Review:

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 and missing data analysis in epidemiology. Illustrative examples, including real-life research problems 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. Also included are an instructor's guide, student solutions manual, and downloadable data sets. 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 to illustrate the application of R language for biostatistical calculations and graphical displays of results Includes instructor's guide, student solutions manual, and downloadable data sets.

Biostatistics with R

Biostatistics with R
Author: Babak Shahbaba
Publsiher: Springer Science & Business Media
Total Pages: 352
Release: 2011-12-15
ISBN 10: 1461413028
ISBN 13: 9781461413028
Language: EN, FR, DE, ES & NL

Biostatistics with R Book Review:

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 this book is an introduction to Bayesian analysis. This author discusses basic statistical analysis through a series of biological examples using R and R-Commander as computational tools. The book is ideal for instructors of basic statistics for biologists and other health scientists. The step-by-step application of statistical methods discussed in this book allows readers, who are interested in statistics and its application in biology, to use the book as a self-learning text.

Research Awards Index

Research Awards Index
Author: Anonim
Publsiher: Unknown
Total Pages: 135
Release: 1989
ISBN 10: 1928374650XXX
ISBN 13: UOM:39015014022589
Language: EN, FR, DE, ES & NL

Research Awards Index Book Review:

Biomedical Index to PHS supported Research

Biomedical Index to PHS supported Research
Author: Anonim
Publsiher: Unknown
Total Pages: 135
Release: 1989
ISBN 10: 1928374650XXX
ISBN 13: UOM:39015015076972
Language: EN, FR, DE, ES & NL

Biomedical Index to PHS supported Research Book Review:

Cognitive and Soft Computing Techniques for the Analysis of Healthcare Data

Cognitive and Soft Computing Techniques for the Analysis of Healthcare Data
Author: Akash Kumar Bhoi,Victor Hugo Costa de Albuquerque,Parvathaneni Naga Srinivasu,Goncalo Marques
Publsiher: Academic Press
Total Pages: 294
Release: 2022-01-28
ISBN 10: 0323903487
ISBN 13: 9780323903486
Language: EN, FR, DE, ES & NL

Cognitive and Soft Computing Techniques for the Analysis of Healthcare Data Book Review:

Cognitive and Soft Computing Techniques for the Analysis of Healthcare Data discusses the insight of data processing applications in various domains through soft computing techniques and enormous advancements in the field. The book focuses on the cross-disciplinary mechanisms and ground-breaking research ideas on novel techniques and data processing approaches in handling structured and unstructured healthcare data. It also gives insight into various information-processing models and many memories associated with it while processing the information for forecasting future trends and decision making. This book is an excellent resource for researchers and professionals who work in the Healthcare Industry, Data Science, and Machine learning. Focuses on data-centric operations in the Healthcare industry Provides the latest trends in healthcare data analytics and practical implementation outcomes of the proposed models Addresses real-time challenges and case studies in the Healthcare industry

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
Publsiher: CRC Press
Total Pages: 378
Release: 2017-06-01
ISBN 10: 1351651145
ISBN 13: 9781351651141
Language: EN, FR, DE, ES & NL

Clinical Trial Data Analysis Using R and SAS Book Review:

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 and SAS, Second Edition provides a thorough presentation of biostatistical analyses of clinical trial data with step-by-step implementations using R and SAS. The book’s practical, detailed approach draws on the authors’ 30 years’ experience in biostatistical research and clinical development. The authors develop step-by-step analysis code using appropriate R packages and functions and SAS PROCS, which enables readers to gain an understanding of the analysis methods and R and SAS implementation so that they can use these two popular software packages to analyze their own clinical trial data. What’s New in the Second Edition Adds SAS programs along with the R programs for clinical trial data analysis. Updates all the statistical analysis with updated R packages. Includes correlated data analysis with multivariate analysis of variance. Applies R and SAS to clinical trial data from hypertension, duodenal ulcer, beta blockers, familial andenomatous polyposis, and breast cancer trials. Covers the biostatistical aspects of various clinical trials, including treatment comparisons, time-to-event endpoints, longitudinal clinical trials, and bioequivalence trials.

Biostatistics

Biostatistics
Author: Wayne W. Daniel,Chad L. Cross
Publsiher: Wiley
Total Pages: 720
Release: 2018-11-13
ISBN 10: 1119282373
ISBN 13: 9781119282372
Language: EN, FR, DE, ES & NL

Biostatistics Book Review:

The ability to analyze and interpret enormous amounts of data has become a prerequisite for success in allied healthcare and the health sciences. Now in its 11th edition, Biostatistics: A Foundation for Analysis in the Health Sciences continues to offer in-depth guidance toward biostatistical concepts, techniques, and practical applications in the modern healthcare setting. Comprehensive in scope yet detailed in coverage, this text helps students understand—and appropriately use—probability distributions, sampling distributions, estimation, hypothesis testing, variance analysis, regression, correlation analysis, and other statistical tools fundamental to the science and practice of medicine. Clearly-defined pedagogical tools help students stay up-to-date on new material, and an emphasis on statistical software allows faster, more accurate calculation while putting the focus on the underlying concepts rather than the math. Students develop highly relevant skills in inferential and differential statistical techniques, equipping them with the ability to organize, summarize, and interpret large bodies of data. Suitable for both graduate and advanced undergraduate coursework, this text retains the rigor required for use as a professional reference.

Longitudinal Data Analysis for the Behavioral Sciences Using R

Longitudinal Data Analysis for the Behavioral Sciences Using R
Author: Jeffrey D. Long
Publsiher: SAGE
Total Pages: 542
Release: 2011-10-31
ISBN 10: 1412982685
ISBN 13: 9781412982689
Language: EN, FR, DE, ES & NL

Longitudinal Data Analysis for the Behavioral Sciences Using R Book Review:

This book is unique in its focus on showing students in the behavioral sciences how to analyze longitudinal data using R software. The book focuses on application, making it practical and accessible to students in psychology, education, and related fields, who have a basic foundation in statistics. It provides explicit instructions in R computer programming throughout the book, showing students exactly how a specific analysis is carried out and how output is interpreted.

Using R for Introductory Statistics

Using R for Introductory Statistics
Author: John Verzani
Publsiher: CRC Press
Total Pages: 518
Release: 2018-10-03
ISBN 10: 1315360306
ISBN 13: 9781315360300
Language: EN, FR, DE, ES & NL

Using R for Introductory Statistics Book Review:

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 R provides a grounding in the functionality of base R. Discussions of the use of RStudio helps new R users avoid as many pitfalls as possible. Use of knitr package makes code easier to read and therefore easier to reason about. Additional information on computer-intensive approaches motivates the traditional approach. Updated examples and data make the information current and topical. The book has an accompanying package, UsingR, available from CRAN, R’s repository of user-contributed packages. The package contains the data sets mentioned in the text (data(package="UsingR")), answers to selected problems (answers()), a few demonstrations (demo()), the errata (errata()), and sample code from the text. The topics of this text line up closely with traditional teaching progression; however, the book also highlights computer-intensive approaches to motivate the more traditional approach. The authors emphasize realistic data and examples and rely on visualization techniques to gather insight. They introduce statistics and R seamlessly, giving students the tools they need to use R and the information they need to navigate the sometimes complex world of statistical computing.

Health Services Reports

Health Services Reports
Author: Anonim
Publsiher: Unknown
Total Pages: 636
Release: 1974
ISBN 10: 1928374650XXX
ISBN 13: IND:30000097539633
Language: EN, FR, DE, ES & NL

Health Services Reports Book Review:

Public Health Reports

Public Health Reports
Author: Anonim
Publsiher: Unknown
Total Pages: 135
Release: 1974
ISBN 10: 1928374650XXX
ISBN 13: UOM:39015007389201
Language: EN, FR, DE, ES & NL

Public Health Reports Book Review: