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Biostatistical Design And Analysis Using R
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Book Synopsis Biostatistical Design and Analysis Using R by : Dr Murray Logan
Download or read book Biostatistical Design and Analysis Using R written by Dr Murray Logan and published by John Wiley & Sons. This book was released on 2011-09-20 with total page 578 pages. Available in PDF, EPUB and Kindle. Book excerpt: R — the statistical and graphical environment is rapidly emerging as an important set of teaching and research tools for biologists. This book draws upon the popularity and free availability of R to couple the theory and practice of biostatistics into a single treatment, so as to provide a textbook for biologists learning statistics, R, or both. An abridged description of biostatistical principles and analysis sequence keys are combined together with worked examples of the practical use of R into a complete practical guide to designing and analyzing real biological research. Topics covered include: simple hypothesis testing, graphing exploratory data analysis and graphical summaries regression (linear, multi and non-linear) simple and complex ANOVA and ANCOVA designs (including nested, factorial, blocking, spit-plot and repeated measures) frequency analysis and generalized linear models. Linear mixed effects modeling is also incorporated extensively throughout as an alternative to traditional modeling techniques. The book is accompanied by a companion website www.wiley.com/go/logan/r with an extensive set of resources comprising all R scripts and data sets used in the book, additional worked examples, the biology package, and other instructional materials and links.
Book Synopsis Foundational and Applied Statistics for Biologists Using R by : Ken A. Aho
Download or read book Foundational and Applied Statistics for Biologists Using R written by Ken A. Aho and published by CRC Press. This book was released on 2016-03-09 with total page 598 pages. Available in PDF, EPUB and Kindle. Book excerpt: Full of biological applications, exercises, and interactive graphical examples, this text presents comprehensive coverage of both modern analytical methods and statistical foundations. The author harnesses the inherent properties of the R environment to enable students to examine the code of complicated procedures step by step and thus better understand the process of obtaining analysis results. The graphical capabilities of R are used to provide interactive demonstrations of simple to complex statistical concepts. R code and other materials are available online.
Book Synopsis An Introduction to Biostatistics by : Thomas Glover
Download or read book An Introduction to Biostatistics written by Thomas Glover and published by Waveland Press. This book was released on 2015-06-29 with total page 551 pages. Available in PDF, EPUB and Kindle. Book excerpt: For over a decade, Glover and Mitchell have provided life-sciences students with an accessible, complete introduction to the use of statistics in their disciplines. The authors emphasize the relationships between probability, probability distributions, and hypothesis testing using both parametric and nonparametric analyses. Copious examples throughout the text apply concepts and theories to real questions faced by researchers in biology, environmental science, biochemistry, and health sciences. Dozens of examples and problems are new to the Third Edition, as are “Concept Checks”—short questions that allow readers to immediately gauge their mastery of the topics presented. Regardless of mathematical background, all readers will appreciate the value of statistics as a fundamental quantitative skill for the life sciences.
Download or read book The R Book written by Michael J. Crawley and published by John Wiley & Sons. This book was released on 2007-06-13 with total page 953 pages. Available in PDF, EPUB and Kindle. Book excerpt: The high-level language of R is recognized as one of the mostpowerful and flexible statistical software environments, and israpidly becoming the standard setting for quantitative analysis,statistics and graphics. R provides free access to unrivalledcoverage and cutting-edge applications, enabling the user to applynumerous statistical methods ranging from simple regression to timeseries or multivariate analysis. Building on the success of the author’s bestsellingStatistics: An Introduction using R, The R Book ispacked with worked examples, providing an all inclusive guide to R,ideal for novice and more accomplished users alike. The bookassumes no background in statistics or computing and introduces theadvantages of the R environment, detailing its applications in awide range of disciplines. Provides the first comprehensive reference manual for the Rlanguage, including practical guidance and full coverage of thegraphics facilities. Introduces all the statistical models covered by R, beginningwith simple classical tests such as chi-square and t-test. Proceeds to examine more advance methods, from regression andanalysis of variance, through to generalized linear models,generalized mixed models, time series, spatial statistics,multivariate statistics and much more. The R Book is aimed at undergraduates, postgraduates andprofessionals in science, engineering and medicine. It is alsoideal for students and professionals in statistics, economics,geography and the social sciences.
Book Synopsis Biostatistics for Epidemiology and Public Health Using R by : Bertram K.C. Chan, PhD
Download or read book Biostatistics for Epidemiology and Public Health Using R written by Bertram K.C. Chan, PhD and published by Springer Publishing Company. This book was released on 2015-11-05 with total page 460 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. In addition to being freely available, R offers several advantages for biostatistics, including strong graphics capabilities, the ability to write customized functions, and its extensibility. 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-bystep 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 and exercises 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. This text is supplemented with teaching resources, including an online guide for students in solving exercises and an instructor's manual. 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 and exercises to illustrate the application of R language for biostatistical calculations and graphical displays of results Includes online student solutions guide and instructor's manual
Book Synopsis Introductory Statistics with R by : Peter Dalgaard
Download or read book Introductory Statistics with R written by Peter Dalgaard and published by Springer Science & Business Media. This book was released on 2008-06-27 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an elementary-level introduction to R, targeting both non-statistician scientists in various fields and students of statistics. The main mode of presentation is via code examples with liberal commenting of the code and the output, from the computational as well as the statistical viewpoint. Brief sections introduce the statistical methods before they are used. A supplementary R package can be downloaded and contains the data sets. All examples are directly runnable and all graphics in the text are generated from the examples. The statistical methodology covered includes statistical standard distributions, one- and two-sample tests with continuous data, regression analysis, one-and two-way analysis of variance, regression analysis, analysis of tabular data, and sample size calculations. In addition, the last four chapters contain introductions to multiple linear regression analysis, linear models in general, logistic regression, and survival analysis.
Download or read book Biostatistics with R written by Jan Lepš and published by Cambridge University Press. This book was released on 2020-07-30 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: A straightforward introduction to a wide range of statistical methods for field biologists, using thoroughly explained R code.
Book Synopsis Clinical Trial Data Analysis Using R and SAS by : Ding-Geng (Din) Chen
Download or read book Clinical Trial Data Analysis Using R and SAS written by Ding-Geng (Din) Chen and published by CRC Press. This book was released on 2017-06-01 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Biostatistical Analysis by : Jerrold H. Zar
Download or read book Biostatistical Analysis written by Jerrold H. Zar and published by Pearson. This book was released on 2018 with total page 960 pages. Available in PDF, EPUB and Kindle. Book excerpt: Zar's Biostatistical Analysis, Fifth Edition is the ideal textbook for graduate and undergraduate students seeking practical coverage of statistical analysis methods used by researchers to collect, summarize, analyze and draw conclusions from biological research. The latest edition of this best-selling textbook is both comprehensive and easy to read. It is suitable as an introduction for beginning students and as a comprehensive reference book for biological researchers and for advanced students. This book is appropriate for a one- or two-semester, junior or graduate-level course in biostatistics, biometry, quantitative biology, or statistics, and assumes a prerequisite of algebra.
Book Synopsis Practicing R for Statistical Computing by : Muhammad Aslam
Download or read book Practicing R for Statistical Computing written by Muhammad Aslam and published by Springer Nature. This book was released on 2023-07-19 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is designed to provide a comprehensive introduction to R programming for data analysis, manipulation and presentation. It covers fundamental data structures such as vectors, matrices, arrays and lists, along with techniques for exploratory data analysis, data transformation and manipulation. The book explains basic statistical concepts and demonstrates their implementation using R, including descriptive statistics, graphical representation of data, probability, popular probability distributions and hypothesis testing. It also explores linear and non-linear modeling, model selection and diagnostic tools in R. The book also covers flow control and conditional calculations by using ‘‘if’’ conditions and loops and discusses useful functions and resources for further learning. It provides an extensive list of functions grouped according to statistics classification, which can be helpful for both statisticians and R programmers. The use of different graphic devices, high-level and low-level graphical functions and adjustment of parameters are also explained. Throughout the book, R commands, functions and objects are printed in a different font for easy identification. Common errors, warnings and mistakes in R are also discussed and classified with explanations on how to prevent them.
Book Synopsis Introduction to Biostatistics by : Ronald N. Forthofer
Download or read book Introduction to Biostatistics written by Ronald N. Forthofer and published by Elsevier. This book was released on 2014-05-19 with total page 586 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Biostatistics course is often found in the schools of public Health, medical schools, and, occasionally, in statistics and biology departments. The population of students in these courses is a diverse one, with varying preparedness. Introduction to Biostatistics assumes the reader has at least two years of high school algebra, but no previous exposure to statistics is required. Written for individuals who might be fearful of mathematics, this book minimizes the technical difficulties and emphasizes the importance of statistics in scientific investigation. An understanding of underlying design and analysis is stressed. The limitations of the research, design and analytical techniques are discussed, allowing the reader to accurately interpret results. Real data, both processed and raw, are used extensively in examples and exercises. Statistical computing packages - MINITAB, SAS and Stata - are integrated. The use of the computer and software allows a sharper focus on the concepts, letting the computer do the necessary number-crunching. - Emphasizes underlying statistical concepts more than competing texts - Focuses on experimental design and analysis, at an elementary level - Includes an introduction to linear correlation and regression - Statistics are central: probability is downplayed - Presents life tables and survival analysis - Appendix with solutions to many exercises - Special instructor's manual with solution to all exercises
Book Synopsis Applied Meta-Analysis with R and Stata by : Ding-Geng (Din) Chen
Download or read book Applied Meta-Analysis with R and Stata written by Ding-Geng (Din) Chen and published by CRC Press. This book was released on 2021-03-31 with total page 423 pages. Available in PDF, EPUB and Kindle. Book excerpt: Review of the First Edition: The authors strive to reduce theory to a minimum, which makes it a self-learning text that is comprehensible for biologists, physicians, etc. who lack an advanced mathematics background. Unlike in many other textbooks, R is not introduced with meaningless toy examples; instead the reader is taken by the hand and shown around some analyses, graphics, and simulations directly relating to meta-analysis... A useful hands-on guide for practitioners who want to familiarize themselves with the fundamentals of meta-analysis and get started without having to plough through theorems and proofs. —Journal of Applied Statistics Statistical Meta-Analysis with R and Stata, Second Edition provides a thorough presentation of statistical meta-analyses (MA) with step-by-step implementations using R/Stata. The authors develop analysis step by step using appropriate R/Stata functions, which enables readers to gain an understanding of meta-analysis methods and R/Stata implementation so that they can use these two popular software packages to analyze their own meta-data. Each chapter gives examples of real studies compiled from the literature. After presenting the data and necessary background for understanding the applications, various methods for analyzing meta-data are introduced. The authors then develop analysis code using the appropriate R/Stata packages and functions. What’s New in the Second Edition: Adds Stata programs along with the R programs for meta-analysis Updates all the statistical meta-analyses with R/Stata programs Covers fixed-effects and random-effects MA, meta-regression, MA with rare-event, and MA-IPD vs MA-SS Adds five new chapters on multivariate MA, publication bias, missing data in MA, MA in evaluating diagnostic accuracy, and network MA Suitable as a graduate-level text for a meta-data analysis course, the book is also a valuable reference for practitioners and biostatisticians (even those with little or no experience in using R or Stata) in public health, medical research, governmental agencies, and the pharmaceutical industry.
Book Synopsis Regression Modeling Strategies by : Frank E. Harrell
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".
Book Synopsis Research Design & Statistical Analysis by : Arnold D. Well
Download or read book Research Design & Statistical Analysis written by Arnold D. Well and published by Psychology Press. This book was released on 2003-01-30 with total page 871 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Free CD contains several real and artificial data sets used in the book in SPSS, SYSTAT, and ASCII formats"--Cover
Book Synopsis Multivariate Statistical Methods by : Bryan F.J. Manly
Download or read book Multivariate Statistical Methods written by Bryan F.J. Manly and published by CRC Press. This book was released on 2016-11-03 with total page 227 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multivariate Statistical Methods: A Primer provides an introductory overview of multivariate methods without getting too deep into the mathematical details. This fourth edition is a revised and updated version of this bestselling introductory textbook. It retains the clear and concise style of the previous editions of the book and focuses on examples from biological and environmental sciences. The major update with this edition is that R code has been included for each of the analyses described, although in practice any standard statistical package can be used. The original idea with this book still applies. This was to make it as short as possible and enable readers to begin using multivariate methods in an intelligent manner. With updated information on multivariate analyses, new references, and R code included, this book continues to provide a timely introduction to useful tools for multivariate statistical analysis.
Book Synopsis Multivariate Statistical Methods by : Jorge A. Navarro
Download or read book Multivariate Statistical Methods written by Jorge A. Navarro and published by CRC Press. This book was released on 2016-11-03 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multivariate Statistical Methods: A Primer provides an introductory overview of multivariate methods without getting too deep into the mathematical details. This fourth edition is a revised and updated version of this bestselling introductory textbook. It retains the clear and concise style of the previous editions of the book and focuses on examples from biological and environmental sciences. The major update with this edition is that R code has been included for each of the analyses described, although in practice any standard statistical package can be used. The original idea with this book still applies. This was to make it as short as possible and enable readers to begin using multivariate methods in an intelligent manner. With updated information on multivariate analyses, new references, and R code included, this book continues to provide a timely introduction to useful tools for multivariate statistical analysis.
Book Synopsis Tracking Environmental Change Using Lake Sediments by : John B.H. Birks
Download or read book Tracking Environmental Change Using Lake Sediments written by John B.H. Birks and published by Springer Science & Business Media. This book was released on 2012-04-08 with total page 751 pages. Available in PDF, EPUB and Kindle. Book excerpt: Numerical and statistical methods have rapidly become part of a palaeolimnologist’s tool-kit. They are used to explore and summarise complex data, reconstruct past environmental variables from fossil assemblages, and test competing hypotheses about the causes of observed changes in lake biota through history. This book brings together a wide array of numerical and statistical techniques currently available for use in palaeolimnology and other branches of palaeoecology. Visit http://extras.springer.com the Springer's Extras website to view data-sets, figures, software, and R scripts used or mentioned in this book.
