Download or read book Analyzing Medical Data Using S PLUS written by Brian Everitt and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 488 pages. Available in PDF, EPUB and Kindle. Book excerpt: Each chapter consists of basic statistical theory, simple examples of S-PLUS code, plus more complex examples of S-PLUS code, and exercises. All data sets are taken from genuine medical investigations and will be available on a web site. The examples in the book contain extensive graphical analysis to highlight one of the prime features of S-PLUS. Written with few details of S-PLUS and less technical descriptions, the book concentrates solely on medical data sets, demonstrating the flexibility of S-PLUS and its huge advantages, particularly for applied medical statisticians.
Download or read book Analyzing Medical Data Using S Plus written by Brian Everitt and published by . This book was released on 2014-01-15 with total page 500 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Regression Modeling Strategies written by Frank E. Harrell and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 583 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many texts are excellent sources of knowledge about individual statistical tools, but the art of data analysis is about choosing and using multiple tools. Instead of presenting isolated techniques, this text emphasizes problem solving strategies that address the many issues arising when developing multivariable models using real data and not standard textbook examples. It includes imputation methods for dealing with missing data effectively, methods for dealing with nonlinear relationships and for making the estimation of transformations a formal part of the modeling process, methods for dealing with "too many variables to analyze and not enough observations," and powerful model validation techniques based on the bootstrap. This text realistically deals with model uncertainty and its effects on inference to achieve "safe data mining".
Download or read book Statistical Analysis of Medical Data Using SAS written by Geoff Der and published by CRC Press. This book was released on 2005-09-20 with total page 450 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 a particular analysis method. The authors briefly describe each procedure, but focus on its SAS implementation and properly interpreting the output. The carefully designed presentation relegates the theoretical details to "Displays," so that the code and results can be explored without interruption. All of the code and data sets used in the book are available for download from either the SAS Web site or www.crcpress.com. Der and Everitt, authors of the best-selling Handbook of Statistical Analyses Using SAS, bring all of their considerable talent and experience to bear in this book. Step-by-step instructions, lucid explanations and clear examples combine to form an outstanding, self-contained guide--suitable for medical researchers and statisticians alike--to using SAS to analyze medical data.
Download or read book A Handbook of Statistical Analyses Using S Plus Second Edition written by Brian S Everitt and published by CRC Press. This book was released on 2020-09-30 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since the first edition of this book was published, S-PLUS has evolved markedly with new methods of analysis, new graphical procedures, and a convenient graphical user interface (GUI). Today, S-PLUS is the statistical software of choice for many applied researchers in disciplines ranging from finance to medicine. Combining the command line language and GUI of S-PLUS now makes this book even more suitable for inexperienced users, students, and anyone without the time, patience, or background needed to wade through the many more advanced manuals and texts on the market. The second edition of A Handbook of Statistical Analyses Using S-Plus has been completely revised to provide an outstanding introduction to the latest version of this powerful software system. Each chapter focuses on a particular statistical technique, applies it to one or more data sets, and shows how to generate the proposed analyses and graphics using S-PLUS. The author explains S-PLUS functions from both the Windows and command-line perspectives and clearly demonstrates how to switch between the two. This handbook provides the perfect vehicle for introducing the exciting possibilities S-PLUS, S-PLUS 2000, and S-PLUS 6 hold for data analysis. All of the data sets used in the text, along with script files giving the command language used in each chapter, are available for download from the Internet at http: //www.iop.kcl.ac.uk/iop/Departments/BioComp/splus.shtml
Download or read book Biostatistics and Computer based Analysis of Health Data Using SAS written by Christophe Lalanne and published by Elsevier. This book was released on 2017-06-22 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Download or read book Biostatistics and Computer based Analysis of Health Data using R written by Christophe Lalanne and published by Elsevier. This book was released on 2016-07-13 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Download or read book Biostatistics and Computer based Analysis of Health Data using Stata written by Christophe Lalanne and published by Elsevier. This book was released on 2016-09-06 with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Download or read book The Basics of S PLUS written by Andreas Krause and published by Springer Science & Business Media. This book was released on 2007-11-24 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: In a clear style the most important ideas of S-PLUS are introduced through the use of many examples. Each chapter includes a collection of exercises, fully worked-out solutions and detailed comments.
Download or read book Encyclopaedic Companion to Medical Statistics written by Brian S. Everitt and published by John Wiley & Sons. This book was released on 2011-06-20 with total page 753 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical methodology is of great importance to medical research and clinical practice. The Encyclopaedic Companion to Medical Statistics contains readable accounts of the key topics central to current research and practice. Each entry has been written by an individual chosen for both their expertise in the field and their ability to communicate statistical concepts successfully to medical researchers. Real examples from the biomedical literature and relevant illustrations feature in many entries and extensive cross–referencing signposts the reader to related entries. Key Features: Contains accounts of over 400 statistical topics central to current medical research. 80% of first edition entries updated and revised. Presents the latest techniques used at the cutting edge of medical research. Covers common errors in statistical analyses in medicine. Real examples from the biomedical literature and relevant illustrations feature throughout. Contains contributions from over 70 experts in the field. Medical researchers, researchers and practitioners in medical research and statistics will benefit greatly from this book.
Download or read book Statistical Analysis of Medical Data Using SAS written by Brian S. Der and published by CRC Press. This book was released on 2017-12-13 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 a particular analysis method. The authors briefly describe each procedure, but focus on its SAS implementation and properly interpreting the output. The carefully designed presentation relegates the theoretical details to "Displays," so that the code and results can be explored without interruption. All of the code and data sets used in the book are available for download from either the SAS Web site or www.crcpress.com. Der and Everitt, authors of the best-selling Handbook of Statistical Analyses Using SAS, bring all of their considerable talent and experience to bear in this book. Step-by-step instructions, lucid explanations and clear examples combine to form an outstanding, self-contained guide--suitable for medical researchers and statisticians alike--to using SAS to analyze medical data.
Download or read book Applied Medical Statistics Using SAS written by Geoff Der and published by CRC Press. This book was released on 2012-10-01 with total page 562 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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, longitudinal and survival data analysis, missing data, generalized additive models (GAMs), and Bayesian methods. The book focuses on performing these analyses using SAS, the software package of choice for those analysing medical data. Features Covers the planning stage of medical studies in detail; several chapters contain details of sample size estimation Illustrates methods of randomisation that might be employed for clinical trials Covers topics that have become of great importance in the 21st century, including Bayesian methods and multiple imputation Its breadth and depth, coupled with the inclusion of all the SAS code, make this book ideal for practitioners as well as for a graduate class in biostatistics or public health. Complete data sets, all the SAS code, and complete outputs can be found on an associated website: http://support.sas.com/amsus
Download or read book Analyzing Ecological Data written by Alain Zuur and published by Springer. This book was released on 2007-08-29 with total page 686 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a practical introduction to analyzing ecological data using real data sets. The first part gives a largely non-mathematical introduction to data exploration, univariate methods (including GAM and mixed modeling techniques), multivariate analysis, time series analysis, and spatial statistics. The second part provides 17 case studies. The case studies include topics ranging from terrestrial ecology to marine biology and can be used as a template for a reader’s own data analysis. Data from all case studies are available from www.highstat.com. Guidance on software is provided in the book.
Download or read book Modelling Survival Data in Medical Research Second Edition written by David Collett and published by CRC Press. This book was released on 2003-03-28 with total page 413 pages. Available in PDF, EPUB and Kindle. Book excerpt: Critically acclaimed and resoundingly popular in its first edition, Modelling Survival Data in Medical Research has been thoroughly revised and updated to reflect the many developments and advances--particularly in software--made in the field over the last 10 years. Now, more than ever, it provides an outstanding text for upper-level and graduate courses in survival analysis, biostatistics, and time-to-event analysis.The treatment begins with an introduction to survival analysis and a description of four studies that lead to survival data. Subsequent chapters then use those data sets and others to illustrate the various analytical techniques applicable to such data, including the Cox regression model, the Weibull proportional hazards model, and others. This edition features a more detailed treatment of topics such as parametric models, accelerated failure time models, and analysis of interval-censored data. The author also focuses the software section on the use of SAS, summarising the methods used by the software to generate its output and examining that output in detail. Profusely illustrated with examples and written in the author's trademark, easy-to-follow style, Modelling Survival Data in Medical Research, Second Edition is a thorough, practical guide to survival analysis that reflects current statistical practices.
Download or read book Modelling Binary Data written by David Collett and published by CRC Press. This book was released on 2002-09-25 with total page 397 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since the original publication of the bestselling Modelling Binary Data, a number of important methodological and computational developments have emerged, accompanied by the steady growth of statistical computing. Mixed models for binary data analysis and procedures that lead to an exact version of logistic regression form valuable additions to the
Download or read book Modelling Binary Data Second Edition written by David Collett and published by CRC Press. This book was released on 2002-09-25 with total page 406 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since the original publication of the bestselling Modelling Binary Data, a number of important methodological and computational developments have emerged, accompanied by the steady growth of statistical computing. Mixed models for binary data analysis and procedures that lead to an exact version of logistic regression form valuable additions to the statistician's toolbox, and author Dave Collett has fully updated his popular treatise to incorporate these important advances. Modelling Binary Data, Second Edition now provides an even more comprehensive and practical guide to statistical methods for analyzing binary data. Along with thorough revisions to the original material-now independent of any particular software package- it includes a new chapter introducing mixed models for binary data analysis and another on exact methods for modelling binary data. The author has also added material on modelling ordered categorical data and provides a summary of the leading software packages. All of the data sets used in the book are available for download from the Internet, and the appendices include additional data sets useful as exercises.
Download or read book Modelling Survival Data in Medical Research written by David Collett and published by CRC Press. This book was released on 2015-05-04 with total page 538 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modelling Survival Data in Medical Research describes the modelling approach to the analysis of survival data using a wide range of examples from biomedical research.Well known for its nontechnical style, this third edition contains new chapters on frailty models and their applications, competing risks, non-proportional hazards, and dependent censo
