Robust Methods In Biostatistics

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Robust Methods In Biostatistics
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Author : Stephane Heritier
language : en
Publisher: John Wiley & Sons
Release Date : 2009-05-11
Robust Methods In Biostatistics written by Stephane Heritier and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-05-11 with Medical categories.
Robust statistics is an extension of classical statistics that specifically takes into account the concept that the underlying models used to describe data are only approximate. Its basic philosophy is to produce statistical procedures which are stable when the data do not exactly match the postulated models as it is the case for example with outliers. Robust Methods in Biostatistics proposes robust alternatives to common methods used in statistics in general and in biostatistics in particular and illustrates their use on many biomedical datasets. The methods introduced include robust estimation, testing, model selection, model check and diagnostics. They are developed for the following general classes of models: Linear regression Generalized linear models Linear mixed models Marginal longitudinal data models Cox survival analysis model The methods are introduced both at a theoretical and applied level within the framework of each general class of models, with a particular emphasis put on practical data analysis. This book is of particular use for research students,applied statisticians and practitioners in the health field interested in more stable statistical techniques. An accompanying website provides R code for computing all of the methods described, as well as for analyzing all the datasets used in the book.
Robust Nonparametric Statistical Methods
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Author : Thomas P. Hettmansperger
language : en
Publisher: Hodder Education
Release Date : 1998
Robust Nonparametric Statistical Methods written by Thomas P. Hettmansperger and has been published by Hodder Education this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998 with Mathematics categories.
Based in ranks of the data, this book offers an alternative to the traditional least squares approach. Topics include one- and two-sample location models, linear models (including multiple regression and designed experiments), and multivariate models. Rank tests and estimates for all models are developed, including bounded influence and high breakdown methods. Emphasis is on efficiency and robustness and all methods are illustrated on data sets.
Robust Statistics
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Author : Ricardo A. Maronna
language : en
Publisher: John Wiley & Sons
Release Date : 2018-10-19
Robust Statistics written by Ricardo A. Maronna and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-19 with Mathematics categories.
A new edition of this popular text on robust statistics, thoroughly updated to include new and improved methods and focus on implementation of methodology using the increasingly popular open-source software R. Classical statistics fail to cope well with outliers associated with deviations from standard distributions. Robust statistical methods take into account these deviations when estimating the parameters of parametric models, thus increasing the reliability of fitted models and associated inference. This new, second edition of Robust Statistics: Theory and Methods (with R) presents a broad coverage of the theory of robust statistics that is integrated with computing methods and applications. Updated to include important new research results of the last decade and focus on the use of the popular software package R, it features in-depth coverage of the key methodology, including regression, multivariate analysis, and time series modeling. The book is illustrated throughout by a range of examples and applications that are supported by a companion website featuring data sets and R code that allow the reader to reproduce the examples given in the book. Unlike other books on the market, Robust Statistics: Theory and Methods (with R) offers the most comprehensive, definitive, and up-to-date treatment of the subject. It features chapters on estimating location and scale; measuring robustness; linear regression with fixed and with random predictors; multivariate analysis; generalized linear models; time series; numerical algorithms; and asymptotic theory of M-estimates. Explains both the use and theoretical justification of robust methods Guides readers in selecting and using the most appropriate robust methods for their problems Features computational algorithms for the core methods Robust statistics research results of the last decade included in this 2nd edition include: fast deterministic robust regression, finite-sample robustness, robust regularized regression, robust location and scatter estimation with missing data, robust estimation with independent outliers in variables, and robust mixed linear models. Robust Statistics aims to stimulate the use of robust methods as a powerful tool to increase the reliability and accuracy of statistical modelling and data analysis. It is an ideal resource for researchers, practitioners, and graduate students in statistics, engineering, computer science, and physical and social sciences.
Fundamentals Of Modern Statistical Methods
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Author : Rand R. Wilcox
language : en
Publisher: Springer
Release Date : 2010-03-10
Fundamentals Of Modern Statistical Methods written by Rand R. Wilcox and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-03-10 with Social Science categories.
Conventional statistical methods have a very serious flaw. They routinely miss differences among groups or associations among variables that are detected by more modern techniques, even under very small departures from normality. Hundreds of journal articles have described the reasons standard techniques can be unsatisfactory, but simple, intuitive explanations are generally unavailable. Situations arise where even highly nonsignificant results become significant when analyzed with more modern methods. Without assuming the reader has any prior training in statistics, Part I of this book describes basic statistical principles from a point of view that makes their shortcomings intuitive and easy to understand. The emphasis is on verbal and graphical descriptions of concepts. Part II describes modern methods that address the problems covered in Part I. Using data from actual studies, many examples are included to illustrate the practical problems with conventional procedures and how more modern methods can make a substantial difference in the conclusions reached in many areas of statistical research. The second edition of this book includes a number of advances and insights that have occurred since the first edition appeared. Included are new results relevant to medians, regression, measures of association, strategies for comparing dependent groups, methods for dealing with heteroscedasticity, and measures of effect size.
Robust Statistics
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Author : Frank R. Hampel
language : en
Publisher: John Wiley & Sons
Release Date : 2011-09-20
Robust Statistics written by Frank R. Hampel and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-09-20 with Mathematics categories.
The Wiley-Interscience Paperback Series consists of selectedbooks that have been made more accessible to consumers in an effortto increase global appeal and general circulation. With these newunabridged softcover volumes, Wiley hopes to extend the lives ofthese works by making them available to future generations ofstatisticians, mathematicians, and scientists. "This is a nice book containing a wealth of information, much ofit due to the authors. . . . If an instructor designing such acourse wanted a textbook, this book would be the best choiceavailable. . . . There are many stimulating exercises, and the bookalso contains an excellent index and an extensive list ofreferences." —Technometrics "[This] book should be read carefully by anyone who isinterested in dealing with statistical models in a realisticfashion." —American Scientist Introducing concepts, theory, and applications, RobustStatistics is accessible to a broad audience, avoidingallusions to high-powered mathematics while emphasizing ideas,heuristics, and background. The text covers the approach based onthe influence function (the effect of an outlier on an estimater,for example) and related notions such as the breakdown point. Italso treats the change-of-variance function, fundamental conceptsand results in the framework of estimation of a single parameter,and applications to estimation of covariance matrices andregression parameters.
Regression Methods In Biostatistics
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Author : Eric Vittinghoff
language : en
Publisher: Springer Science & Business Media
Release Date : 2012
Regression Methods In Biostatistics written by Eric Vittinghoff and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with Education categories.
This fresh edition, substantially revised and augmented, provides a unified, in-depth, readable introduction to the multipredictor regression methods most widely used in biostatistics. The examples used, analyzed using Stata, can be applied to other areas.
Scan Statistics
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Author : Joseph Glaz
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-12-24
Scan Statistics written by Joseph Glaz and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-12-24 with Mathematics categories.
Scan statistics is currently one of the most active and important areas of research in applied probability and statistics, having applications to a wide variety of fields: archaeology, astronomy, bioinformatics, biosurveillance, molecular biology, genetics, computer science, electrical engineering, geography, material sciences, physics, reconnaissance, reliability and quality control, telecommunication, and epidemiology. Filling a gap in the literature, this self-contained volume brings together a collection of selected chapters illustrating the depth and diversity of theory, methods and applications in the area of scan statistics.
Developments In Robust Statistics
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Author : Rudolf Dutter
language : en
Publisher: Springer Science & Business Media
Release Date : 2003
Developments In Robust Statistics written by Rudolf Dutter and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Business & Economics categories.
Aspects of Robust Statistics are important in many areas. Based on the International Conference on Robust Statistics 2001 (ICORS 2001) in Vorau, Austria, this volume discusses future directions of the discipline, bringing together leading scientists, experienced researchers and practitioners, as well as younger researchers. The papers cover a multitude of different aspects of Robust Statistics. For instance, the fundamental problem of data summary (weights of evidence) is considered and its robustness properties are studied. Further theoretical subjects include e.g.: robust methods for skewness, time series, longitudinal data, multivariate methods, and tests. Some papers deal with computational aspects and algorithms. Finally, the aspects of application and programming tools complete the volume.
Biostatistics
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Author : Wayne W. Daniel
language : en
Publisher: John Wiley & Sons
Release Date : 2018-11-13
Biostatistics written by Wayne W. Daniel and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-13 with Medical categories.
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.
Large Sample Methods In Statistics 1994
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Author : Pranab K. Sen
language : en
Publisher: CRC Press
Release Date : 2017-11-22
Large Sample Methods In Statistics 1994 written by Pranab K. Sen and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-22 with Mathematics categories.
This text bridges the gap between sound theoretcial developments and practical, fruitful methodology by providing solid justification for standard symptotic statistical methods. It contains a unified survey of standard large sample theory and provides access to more complex statistical models that arise in diverse practical applications.