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Xiao-Hua Zhou Statistical Methods in Diagnostic Medicine


An important role of diagnostic medicine research is to estimate and compare the accuracies of diagnostic tests. This book provides a comprehensive account of statistical methods for design and analysis of diagnostic studies, including sample size calculations, estimation of the accuracy of a diagnostic test, comparison of accuracies of competing diagnostic tests, and regression analysis of diagnostic accuracy data. Discussing recently developed methods for correction of verification bias and imperfect reference bias, methods for analysis of clustered diagnostic accuracy data, and meta-analysis methods, Statistical Methods in Diagnostic Medicine explains: * Common measures of diagnostic accuracy and designs for diagnostic accuracy studies * Methods of estimation and hypothesis testing of the accuracy of diagnostic tests * Meta-analysis * Advanced analytic techniques-including methods for comparing correlated ROC curves in multi-reader studies, correcting verification bias, and correcting when an imperfect gold standard is used Thoroughly detailed with numerous applications and end-of-chapter problems as well as a related FTP site providing FORTRAN program listings, data sets, and instructional hints, Statistical Methods in Diagnostic Medicine is a valuable addition to the literature of the field, serving as a much-needed guide for both clinicians and advanced students.

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Группа авторов Statistical Models and Methods for Reliability and Survival Analysis


Statistical Models and Methods for Reliability and Survival Analysis brings together contributions by specialists in statistical theory as they discuss their applications providing up-to-date developments in methods used in survival analysis, statistical goodness of fit, stochastic processes for system reliability, amongst others. Many of these are related to the work of Professor M. Nikulin in statistics over the past 30 years. The authors gather together various contributions with a broad array of techniques and results, divided into three parts – Statistical Models and Methods, Statistical Models and Methods in Survival Analysis, and Reliability and Maintenance. The book is intended for researchers interested in statistical methodology and models useful in survival analysis, system reliability and statistical testing for censored and non-censored data.

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Rand R. Wilcox Understanding and Applying Basic Statistical Methods Using R


Features a straightforward and concise resource for introductory statistical concepts, methods, and techniques using R Understanding and Applying Basic Statistical Methods Using R uniquely bridges the gap between advances in the statistical literature and methods routinely used by non-statisticians. Providing a conceptual basis for understanding the relative merits and applications of these methods, the book features modern insights and advances relevant to basic techniques in terms of dealing with non-normality, outliers, heteroscedasticity (unequal variances), and curvature. Featuring a guide to R, the book uses R programming to explore introductory statistical concepts and standard methods for dealing with known problems associated with classic techniques. Thoroughly class-room tested, the book includes sections that focus on either R programming or computational details to help the reader become acquainted with basic concepts and principles essential in terms of understanding and applying the many methods currently available. Covering relevant material from a wide range of disciplines, Understanding and Applying Basic Statistical Methods Using R also includes: Numerous illustrations and exercises that use data to demonstrate the practical importance of multiple perspectives Discussions on common mistakes such as eliminating outliers and applying standard methods based on means using the remaining data Detailed coverage on R programming with descriptions on how to apply both classic and more modern methods using R A companion website with the data and solutions to all of the exercises Understanding and Applying Basic Statistical Methods Using R is an ideal textbook for an undergraduate and graduate-level statistics courses in the science and/or social science departments. The book can also serve as a reference for professional statisticians and other practitioners looking to better understand modern statistical methods as well as R programming. Rand R. Wilcox, PhD, is Professor in the Department of Psychology at the University of Southern California, Fellow of the Association for Psychological Science, and an associate editor for four statistics journals. He is also a member of the International Statistical Institute. The author of more than 320 articles published in a variety of statistical journals, he is also the author eleven other books on statistics. Dr. Wilcox is creator of WRS (Wilcox’ Robust Statistics), which is an R package for performing robust statistical methods. His main research interest includes statistical methods, particularly robust methods for comparing groups and studying associations.

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Galit Shmueli Statistical Methods in e-Commerce Research


This groundbreaking book introduces the application of statistical methodologies to e-Commerce data With the expanding presence of technology in today's economic market, the use of the Internet for buying, selling, and investing is growing more popular and public in nature. Statistical Methods in e-Commerce Research is the first book of its kind to focus on the statistical models and methods that are essential in order to analyze information from electronic-commerce (e-Commerce) transactions, identify the challenges that arise with new e-Commerce data structures, and discover new knowledge about consumer activity. This collection gathers over thirty researchers and practitioners from the fields of statistics, computer science, information systems, and marketing to discuss the growing use of statistical methods in e-Commerce research. From privacy protection to economic impact, the book first identifies the many obstacles that are encountered while collecting, cleaning, exploring, and analyzing e-Commerce data. Solutions to these problems are then suggested using established and newly developed statistical and data mining methods. Finally, a look into the future of this evolving area of study is provided through an in-depth discussion of the emerging methods for conducting e-Commerce research. Statistical Methods in e-Commerce Research successfully bridges the gap between statistics and e-Commerce, introducing a statistical approach to solving challenges that arise in the context of online transactions, while also introducing a wide range of e-Commerce applications and problems where novel statistical methodology is warranted. It is an ideal text for courses on e-Commerce at the upper-undergraduate and graduate levels and also serves as a valuable reference for researchers and analysts across a wide array of subject areas, including economics, marketing, and information systems who would like to gain a deeper understanding of the use of statistics in their work.

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Hengqing Tong Developing Econometrics


Statistical Theories and Methods with Applications to Economics and Business highlights recent advances in statistical theory and methods that benefit econometric practice. It deals with exploratory data analysis, a prerequisite to statistical modelling and part of data mining. It provides recently developed computational tools useful for data mining, analysing the reasons to do data mining and the best techniques to use in a given situation. Provides a detailed description of computer algorithms. Provides recently developed computational tools useful for data mining Highlights recent advances in statistical theory and methods that benefit econometric practice. Features examples with real life data. Accompanying software featuring DASC (Data Analysis and Statistical Computing). Essential reading for practitioners in any area of econometrics; business analysts involved in economics and management; and Graduate students and researchers in economics and statistics.

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Machin David Regression Methods for Medical Research


Regression Methods for Medical Research provides medical researchers with the skills they need to critically read and interpret research using more advanced statistical methods. The statistical requirements of interpreting and publishing in medical journals, together with rapid changes in science and technology, increasingly demands an understanding of more complex and sophisticated analytic procedures. The text explains the application of statistical models to a wide variety of practical medical investigative studies and clinical trials. Regression methods are used to appropriately answer the key design questions posed and in so doing take due account of any effects of potentially influencing co-variables. It begins with a revision of basic statistical concepts, followed by a gentle introduction to the principles of statistical modelling. The various methods of modelling are covered in a non-technical manner so that the principles can be more easily applied in everyday practice. A chapter contrasting regression modelling with a regression tree approach is included. The emphasis is on the understanding and the application of concepts and methods. Data drawn from published studies are used to exemplify statistical concepts throughout. Regression Methods for Medical Research is especially designed for clinicians, public health and environmental health professionals, para-medical research professionals, scientists, laboratory-based researchers and students.

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Ingvar Eidhammer Computational and Statistical Methods for Protein Quantification by Mass Spectrometry


The definitive introduction to data analysis in quantitative proteomics This book provides all the necessary knowledge about mass spectrometry based proteomics methods and computational and statistical approaches to pursue the planning, design and analysis of quantitative proteomics experiments. The author’s carefully constructed approach allows readers to easily make the transition into the field of quantitative proteomics. Through detailed descriptions of wet-lab methods, computational approaches and statistical tools, this book covers the full scope of a quantitative experiment, allowing readers to acquire new knowledge as well as acting as a useful reference work for more advanced readers. Computational and Statistical Methods for Protein Quantification by Mass Spectrometry: Introduces the use of mass spectrometry in protein quantification and how the bioinformatics challenges in this field can be solved using statistical methods and various software programs. Is illustrated by a large number of figures and examples as well as numerous exercises. Provides both clear and rigorous descriptions of methods and approaches. Is thoroughly indexed and cross-referenced, combining the strengths of a text book with the utility of a reference work. Features detailed discussions of both wet-lab approaches and statistical and computational methods. With clear and thorough descriptions of the various methods and approaches, this book is accessible to biologists, informaticians, and statisticians alike and is aimed at readers across the academic spectrum, from advanced undergraduate students to post doctorates entering the field.

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William Meeker Q. Statistical Methods for Reliability Data


Amstat News asked three review editors to rate their top five favorite books in the September 2003 issue. Statistical Methods for Reliability Data was among those chosen. Bringing statistical methods for reliability testing in line with the computer age This volume presents state-of-the-art, computer-based statistical methods for reliability data analysis and test planning for industrial products. Statistical Methods for Reliability Data updates and improves established techniques as it demonstrates how to apply the new graphical, numerical, or simulation-based methods to a broad range of models encountered in reliability data analysis. It includes methods for planning reliability studies and analyzing degradation data, simulation methods used to complement large-sample asymptotic theory, general likelihood-based methods of handling arbitrarily censored data and truncated data, and more. In this book, engineers and statisticians in industry and academia will find: A wealth of information and procedures developed to give products a competitive edge Simple examples of data analysis computed with the S-PLUS system-for which a suite of functions and commands is available over the Internet End-of-chapter, real-data exercise sets Hundreds of computer graphics illustrating data, results of analyses, and technical concepts An essential resource for practitioners involved in product reliability and design decisions, Statistical Methods for Reliability Data is also an excellent textbook for on-the-job training courses, and for university courses on applied reliability data analysis at the graduate level. An Instructor's Manual presenting detailed solutions to all the problems in the book is available upon requestfrom the Wiley editorial department.

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Xiao-Hua Andrew Zhou's Home Page - University of Washington

Xiao-Hua (Andrew) Zhou,Ph.D Professor, Department of Biostatistics School of Public Health Adjunct Professor, Department of Psychiatry and Behavioral Science School of Medicine University of Washington Director and Research Career Scientist, Biostatistics Unit U.S. Department of Veterans Affairs Seattle Medical Center email: [email protected] office: Met Park West #1400, Puget Care System ...

Statistical Methods in Diagnostic Medicine Wiley Series in ...

Xiao-Hua Zhou, PhD, is Professor of Biostatistics at the University of Washington and Director and Research Career Scientist at the Biostatistics Unit of the Veterans Affairs Puget Sound Healthcare System. He is a Fellow of the American Statistical Association and the author of more than 100 published articles on statistical methods in diagnostic medicine and causal inferences. Nancy A ...

Statistical Methods in Diagnostic Medicine - Xiao-Hua Zhou ...

Statistical Methods in Diagnostic Medicine, Second Edition continues to provide a comprehensive approach to the topic, guiding readers through the necessary practices for understanding these studies and generalizing the results to patient populations. Following a basic introduction to measuring test accuracy and study design, the authors successfully define various measures of diagnostic ...

Statistical Methods in Diagnostic Medicine - Xiao-Hua Zhou ...

Statistical Methods in Diagnostic Medicine, Second Edition continues to provide a comprehensive approach to the topic, guiding readers through the necessary practices for understanding these studies and generalizing the results to patient populations. Following a basic introduction to measuring test accuracy and study design, the authors successfully define various measures of diagnostic ...

Statistical Methods in Diagnostic Medicine - Xiao-Hua Zhou ...

XIAO-HUA ANDREW ZHOU is Associate Professor in the Department of Biostatistics at Indiana University's School of Medicine. NANCY A. OBUCHOWSKI is Associate Staff at the Cleveland Clinic Foundation. DONNA K. McCLISH is Associate Professor of Biostatistics at Virginia Commonwealth University's Medical College of Virginia. Bibliographic information. Title: Statistical Methods in Diagnostic ...

Statistical Methods in Diagnostic Medicine | Wiley Series ...

Xiao-Hua Zhou, PhD, is Professor of Biostatistics at the University of Washington and Director and Research Career Scientist at the Biostatistics Unit of the Veterans Affairs Puget Sound Healthcare System. He is a Fellow of the American Statistical Association and the author of more than 100 published articles on statistical methods in diagnostic medicine and causal inferences.

Xiao-Hua Zhou | Biostatistics

University of Washington School of Public Health. Connect with us: Facebook

By Zhou, Xiao-Hua Author Statistical Methods in Diagnostic ...

By Zhou, Xiao-Hua ( Author ) [ Statistical Methods in Diagnostic Medicine (Wiley Series in Probability and Statistics) - Greenlight ] Mar - 2011 { Hardcover } | Zhou, Xiao-Hua | ISBN: | Kostenloser Versand für alle Bücher mit Versand und Verkauf duch Amazon.

Xiao-Hua Zhou's research works | Peking University ...

Xiao-Hua Zhou's 261 research works with 8,043 citations and 8,017 reads, including: More Accurate Estimates of the Accuracy of RT-PCR and Chest CT Tests for COVID-19

Xiao-Hua Zhou's research works | Peking University ...

Xiao-Hua Zhou's 6 research works with 93 citations and 3,421 reads, including: Prediction of the COVID-19 outbreak based on a realistic stochastic model

Xiaohua Zhou - Home

School of Statistics, Renmin University of China, Beijing, China, Xiaohua Zhou. Department of Biostatistics, University of Washington and HSR&D Center of Excellence, VA Puget Sound Health Care System, WA, USA , Qingzhao Zhang. School of Economics and the Wang Yanan Institute for Studies in Economics, Xiamen University, Xiamen, China February 2017 Journal of Multivariate Analysis, Volume 154 ...

Xiao-Hua Zhou | Biostatistics

Statistical Genetics. Certificate; Training Grant; Certficates & Other Options. Taking Courses with Non-Matriculated Status; Courses & Registration. Course Listings; Introductory Course Sequences; Careers; Apply. Dates & Deadlines; Admission Requirements; Application Instructions; Costs & Funding; Student Experience. Our Approach; Seattle and ...

Statistical Methods in Diagnostic Medicine: 9780470183144 ...

This item: Statistical Methods in Diagnostic Medicine by Xiao-Hua Zhou Hardcover $117.04. Only 1 left in stock - order soon. Ships from and sold by -TextbookRush-. The Statistical Evaluation of Medical Tests for Classification and Prediction (Oxford Statistical … by Margaret Sullivan Pepe Paperback $90.98. In stock. Ships from and sold by allnewbooks. Customers who bought this item also ...

Statistical Methods in Diagnostic Medicine by Xiao-Hua Zhou

Statistical Methods in Diagnostic Medicine book. Read reviews from world’s largest community for readers. Praise for the First Edition . . . the book i...

Statistical Methods in Diagnostic Medicine (eBook, PDF ...

Xiao-Hua Zhou, PhD, is Professor of Biostatistics at theUniversity of Washington and Director and Research Career Scientistat the Biostatistics Unit of the Veterans Affairs Puget SoundHealthcare System. He is a Fellow of the American StatisticalAssociation and the author of more than 100 published articles onstatistical methods in diagnostic medicine and causal inferences. Nancy A. Obuchowski ...

Statistical Methods in Diagnostic Medicine by Zhou, Xiao ...

Statistical Methods in Diagnostic Medicine (Wiley Series in Probability and Statistics series) by Xiao-Hua Zhou. An important role of diagnostic medicine research is to estimate and compare the accuracies of diagnostic tests. This book provides a comprehensive account of statistical methods for design and analysis of diagnostic studies, including sample size calculations, estimation of the ...

Correcting for verification bias in studies of a ...

Xiao-Hua Zhou. Statistical Methods in Medical Research 1998 7: 4, 337-353 Download Citation . If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click on download. Format: Tips on citation download: Download Citation: Download article citation data for ...

Methods to control the empirical type I error rate in ...

Yuhao Deng and Xiao-Hua Zhou. Statistical Methods in Medical Research 2019 29: 6, 1650-1667 Share. Share. Social Media; Email; Share Access; Share this article via social media. The e-mail addresses that you supply to use this service will not be used for any other purpose without your consent. Recommend to a friend Email a link to the following content: * Recipient's Email Address: * Your ...

Xiaohua Zhou-北京大学公共卫生学院 - pku.edu.cn

Annals of Applied Statistics 2018; 12: 1204-1227. 2. Sheng E., Li W., and Zhou XH*. Estimating causal effects of treatment in RCTs with provider and subject noncompliance. Statistics in Medicine. , 38, 5, (738-750), (2018). 3. Fan Y, He M, Su L, and Zhou XH*. A Smoothed Q-Learning Algorithm for Estimating Optimal Dynamic Treatment Regimes ...

) with Application to Medicine - PUUMA

Xiao-Hua Andrew Zhou, Ph.D Chair Professor and Chair, Department of Biostatistics, Peking University Oct 31, 2019 1/22. Definition of Intelligence Intelligence can be generally described as the ability to perceive information, and retain it as knowledge to be applied towards adaptive behaviors within an environment or context. AI: Any device that perceives its environment and takes actions ...

Statistical Methods in Diagnostic Medicine : Xiao-Hua Zhou ...

Xiao-Hua Zhou, PhD, is Professor of Biostatistics at the University of Washington and Director and Research Career Scientist at the Biostatistics Unit of the Veterans Affairs Puget Sound Healthcare System. He is a Fellow of the American Statistical Association and the author of more than 100 published articles on statistical methods in diagnostic medicine and causal inferences. Nancy A ...

Xiao‐Hua Zhou - AI Profile

Xiao‐Hua Zhou, , undefined... Home Research-feed Channel Rankings GCT THU AI TR Open Data Must Reading. Research Feed. Log in AMiner. Academic Profile User Profile. Research Feed My following Paper Collections. views: 5. Update Photo. Xiao‐Hua Zhou. Follow. Sign in to view more. Show Academic Trajectory. Ego Network. D-Core. Research Interests. Author Statistics. Experience . Sign in to ...

Mental Health Biostatistics Training - Xiao-Hua Zhou

Joining with the Department of Psychiatry and Behavioral Sciences, the Department of Biostatistics at the University of Washington proposes a renewal of the predoctoral training program in biostatisti...

Xiaohua Zhou - Home

Xiaohua Zhou. Search for Xiaohua Zhou's work. Search Search. Home Xiaohua Zhou. Xiaohua Zhou. Skip slideshow. Most frequent co-Author ...

Applied Missing Data Analysis in the Health Sciences ...

Applied Missing Data Analysis in the Health Sciences (Statistics in Practice Book 81) - Kindle edition by Zhou, Xiao-Hua, Zhou, Chuan, Lui, Danping, Ding, Xaiobo. Download it once and read it on your Kindle device, PC, phones or tablets. Use features like bookmarks, note taking and highlighting while reading Applied Missing Data Analysis in the Health Sciences (Statistics in Practice Book 81).

Xiao-Hua Zhou (Author of Statistical Methods in Diagnostic ...

Xiao-Hua Zhou is the author of Statistical Methods in Diagnostic Medicine (4.00 avg rating, 2 ratings, 1 review, published 2002), Statistical Methods in ...

Statistical Methods in Diagnostic Medicine: Zhou, Xiao-Hua ...

Statistical Methods in Diagnostic Medicine: Zhou, Xiao-Hua, Obuchowski, Nancy A., McClish, Donna K.: 9780470183144: Books - Amazon.ca

Examples in book Statistical Methods in Diagnostic ...

Examples in book Statistical Methods in Diagnostic Medicine by Xiao-hua Zhou et.al. Chapter 4 (1) roc.binary(s1, s0, r1, r0, alpha) DESCRIPTION: Function . roc.binary. estimate the sensitivity, specificity and their variances for the binary data. Two types of confidence intervals are calculated, namely asymptotic C.I. and score C.I. The description is on the page 101-104 of the book. USAGE: s1 ...

Zhou, Xiao-Hua [WorldCat Identities]

Statistical methods in diagnostic medicine by Xiao-Hua Zhou ( ) 37 editions published between 2002 and 2014 in English and Undetermined and held by 1,197 WorldCat member libraries worldwide

Royal Statistical Society Publications

Xiao-Hua Zhou, Inferences about population means of health care costs, Statistical Methods in Medical Research, 10.1191/0962280202sm290ra, 11, 4, (327-339), (2016). Crossref Xiao-Hua Andrew Zhou, Scott Ramsey, Assessing the equality of means of healthcare costs, Expert Review of Pharmacoeconomics & Outcomes Research, 10.1586/14737167.3.5.561, 3 , 5, (561-567), (2014).

Xiao-Hua Zhou | LibraryThing

Xiao-Hua Zhou, author of Statistical Methods in Diagnostic Medicine, on LibraryThing

Probability Theory and Statistical Inference: Xing Zhao ...

Probability Theory and Statistical Inference: Xing Zhao, Xiao-Hua Zhou, Et Al ,: Amazon.com.au: Books

Statistical methods in diagnostic medicine by Zhou, Xiao ...

Zhou, Xiao-Hua; Obuchowski, Nancy A; McClish, Donna K. This is a comprehensive account of statistical methods for the design and analysis of diagnostic studies, including sample-size calculations, estimation of the accuracy of a diagnostic test and comparison of the relative accuracies of competing diagnostic tests. eBook, Hardback, Electronic resource, Book. English. All formats and editions ...

Statistical Methods in Diagnostic Medicine Wiley Series in ...

Statistical Methods in Diagnostic Medicine Wiley Series in Probability and Statistics: Amazon.es: Xiao-Hua Zhou, Nancy A. Obuchowski, Donna K. McClish: Libros en idiomas extranjeros

Statistical Medicine 2e by Xiao-Hua Zhou: New | eBay

Share - Statistical Medicine 2e by Xiao-Hua Zhou: New. Statistical Medicine 2e by Xiao-Hua Zhou: New. $137.33 + $3.99 Shipping. Get it by Wednesday, Jul 15 from Sparks, Nevada; Need it faster? More shipping options available at checkout • Brand New condition • 30 day returns - Buyer pays return shipping ...

Statistical Methods in Diagnostic Medicine (eBook, PDF ...

An important role of diagnostic medicine research is to estimate and compare the accuracies of diagnostic tests. This book provides a comprehensive account of statistical methods for design and analysis of diagnostic studies, including sample size calculations, estimation of the accuracy of a diagnostic test, comparison of accuracies of competing diagnostic tests, and regression analysis of ...

Zhou, Xiao-Hua | onAcademic

Zhou, Xiao-Hua Liu, Jian-Lin Zhang, Sheng-Li Cell or vesicle adhesion plays an essential role in a plethora of physiological activities. In this study, we established a theoretical model to explore the adhesion behavior of a vesicle adhering on an elastic substrate. Based upon the free energy functional of the system, the governing equation set and the transversality boundary conditions were ...

Suchergebnisse - Wiley-VCH eBooks

Applied Missing Data Analysis in the Health Sciences von: Xiao-Hua Zhou, Chuan Zhou, Danping Lui, Xaiobo Ding

Statistical Methods in Diagnostic Medicine / Edition 2 by ...

Xiao-Hua Zhou, PhD, is Professor of Biostatistics at the University of Washington and Director and Research Career Scientist at the Biostatistics Unit of the Veterans Affairs Puget Sound Healthcare System. He is a Fellow of the American Statistical Association and the author of more than 100 published articles on statistical methods in diagnostic medicine and causal inferences.

Suchergebnisse - "Statistics"

author_facet:"Zhou, Xiao-Hua" author_facet:"Su, Hsiu-Yuan" Treffer 1 - 1 von 1 für Suche '"Statistics"', Suchdauer: 0,33s . Treffer pro Seite. Sortieren. Anzahl Treffer: 1. Online-Ressource . Interval estimation for the difference in paired areas under the ROC curves in the ...

Author: "Zhou, Xiao-Hua" - PubAg Search Results

You searched for: Author "Zhou, Xiao-Hua" Remove constraint Author: "Zhou, Xiao-Hua" Start Over. Toggle facets Limit your search Text Availability. Citation in PubAg 9; Full Text 5; Journal. Biometrics 6; Journal of the Royal Statistical Society 3; Computational statistics & data analysis 2; Colloids and surfaces 1; Journal of econometrics 1; more Journal » Publication Year. 2020 1; 2017 1 ...

Suchergebnisse - ebooks4succes

Applied Missing Data Analysis in the Health Sciences von: Xiao-Hua Zhou, Chuan Zhou, Danping Lui, Xaiobo DingXiao-Hua Zhou, Chuan Zhou, Danping Lui, Xaiobo Ding

楽天ブックス: Statistical Medicine 2e - Xiao-Hua Zhou ...

Statistical Medicine 2e - Xiao-Hua Zhou - 洋書の購入は楽天ブックスで。全品送料無料!購入毎に「楽天ポイント」が貯まってお得!みんなのレビュー・感想も満載。

Jochen Voss An Introduction to Statistical Computing. A Simulation-based Approach


A comprehensive introduction to sampling-based methods in statistical computing The use of computers in mathematics and statistics has opened up a wide range of techniques for studying otherwise intractable problems. Sampling-based simulation techniques are now an invaluable tool for exploring statistical models. This book gives a comprehensive introduction to the exciting area of sampling-based methods. An Introduction to Statistical Computing introduces the classical topics of random number generation and Monte Carlo methods. It also includes some advanced methods such as the reversible jump Markov chain Monte Carlo algorithm and modern methods such as approximate Bayesian computation and multilevel Monte Carlo techniques An Introduction to Statistical Computing: Fully covers the traditional topics of statistical computing. Discusses both practical aspects and the theoretical background. Includes a chapter about continuous-time models. Illustrates all methods using examples and exercises. Provides answers to the exercises (using the statistical computing environment R); the corresponding source code is available online. Includes an introduction to programming in R. This book is mostly self-contained; the only prerequisites are basic knowledge of probability up to the law of large numbers. Careful presentation and examples make this book accessible to a wide range of students and suitable for self-study or as the basis of a taught course

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Fabrizio Ruggeri Statistical Methods in Healthcare


In recent years the number of innovative medicinal products and devices submitted and approved by regulatory bodies has declined dramatically. The medical product development process is no longer able to keep pace with increasing technologies, science and innovations and the goal is to develop new scientific and technical tools and to make product development processes more efficient and effective. Statistical Methods in Healthcare focuses on the application of statistical methodologies to evaluate promising alternatives and to optimize the performance and demonstrate the effectiveness of those that warrant pursuit is critical to success. Statistical methods used in planning, delivering and monitoring health care, as well as selected statistical aspects of the development and/or production of pharmaceuticals and medical devices are also addressed. With a focus on finding solutions to these challenges, this book: Provides a comprehensive, in-depth treatment of statistical methods in healthcare, along with a reference source for practitioners and specialists in health care and drug development. Offers a broad coverage of standards and established methods through leading edge techniques. Uses an integrated, case-study based approach, with focus on applications. Looks at the use of analytical and monitoring schemes to evaluate therapeutic performance. Features the application of modern quality management systems to clinical practice, and to pharmaceutical development and production processes. Addresses the use of modern Statistical methods such as Adaptive Design, Seamless Design, Data Mining, Bayesian networks and Bootstrapping that can be applied to support the challenging new vision. Practitioners in healthcare-related professions, ranging from clinical trials to care delivery to medical device design, as well as statistical researchers in the field, will benefit from this book.

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Reinhard Viertl Statistical Methods for Fuzzy Data


Statistical data are not always precise numbers, or vectors, or categories. Real data are frequently what is called fuzzy. Examples where this fuzziness is obvious are quality of life data, environmental, biological, medical, sociological and economics data. Also the results of measurements can be best described by using fuzzy numbers and fuzzy vectors respectively. Statistical analysis methods have to be adapted for the analysis of fuzzy data. In this book, the foundations of the description of fuzzy data are explained, including methods on how to obtain the characterizing function of fuzzy measurement results. Furthermore, statistical methods are then generalized to the analysis of fuzzy data and fuzzy a-priori information. Key Features: Provides basic methods for the mathematical description of fuzzy data, as well as statistical methods that can be used to analyze fuzzy data. Describes methods of increasing importance with applications in areas such as environmental statistics and social science. Complements the theory with exercises and solutions and is illustrated throughout with diagrams and examples. Explores areas such quantitative description of data uncertainty and mathematical description of fuzzy data. This work is aimed at statisticians working with fuzzy logic, engineering statisticians, finance researchers, and environmental statisticians. It is written for readers who are familiar with elementary stochastic models and basic statistical methods.

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Группа авторов Statistical Models and Methods for Lifetime Data


Praise for the First Edition «An indispensable addition to any serious collection on lifetime data analysis and . . . a valuable contribution to the statistical literature. Highly recommended . . .» -Choice «This is an important book, which will appeal to statisticians working on survival analysis problems.» -Biometrics «A thorough, unified treatment of statistical models and methods used in the analysis of lifetime data . . . this is a highly competent and agreeable statistical textbook.» -Statistics in Medicine The statistical analysis of lifetime or response time data is a key tool in engineering, medicine, and many other scientific and technological areas. This book provides a unified treatment of the models and statistical methods used to analyze lifetime data. Equally useful as a reference for individuals interested in the analysis of lifetime data and as a text for advanced students, Statistical Models and Methods for Lifetime Data, Second Edition provides broad coverage of the area without concentrating on any single field of application. Extensive illustrations and examples drawn from engineering and the biomedical sciences provide readers with a clear understanding of key concepts. New and expanded coverage in this edition includes: * Observation schemes for lifetime data * Multiple failure modes * Counting process-martingale tools * Both special lifetime data and general optimization software * Mixture models * Treatment of interval-censored and truncated data * Multivariate lifetimes and event history models * Resampling and simulation methodology

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Группа авторов Contemporary Bayesian and Frequentist Statistical Research Methods for Natural Resource Scientists


The first all-inclusive introduction to modern statistical research methods in the natural resource sciences The use of Bayesian statistical analysis has become increasingly important to natural resource scientists as a practical tool for solving various research problems. However, many important contemporary methods of applied statistics, such as generalized linear modeling, mixed-effects modeling, and Bayesian statistical analysis and inference, remain relatively unknown among researchers and practitioners in this field. Through its inclusive, hands-on treatment of real-world examples, Contemporary Bayesian and Frequentist Statistical Research Methods for Natural Resource Scientists successfully introduces the key concepts of statistical analysis and inference with an accessible, easy-to-follow approach. The book provides case studies illustrating common problems that exist in the natural resource sciences and presents the statistical knowledge and tools needed for a modern treatment of these issues. Subsequent chapter coverage features: An introduction to the fundamental concepts of Bayesian statistical analysis, including its historical background, conjugate solutions, Bayesian hypothesis testing and decision-making, and Markov Chain Monte Carlo solutions The relevant advantages of using Bayesian statistical analysis, rather than the traditional frequentist approach, to address research problems Two alternative strategies—the a posteriori model selection strategy and the a priori parsimonious model selection strategy using AIC and DIC—to model selection and inference The ideas of generalized linear modeling (GLM), focusing on the most popular GLM of logistic regression An introduction to mixed-effects modeling in S-Plus® and R for analyzing natural resource data sets with varying error structures and dependencies Each statistical concept is accompanied by an illustration of its frequentist application in S-Plus® or R as well as its Bayesian application in WinBUGS. Brief introductions to these software packages are also provided to help the reader fully understand the concepts of the statistical methods that are presented throughout the book. Assuming only a minimal background in introductory statistics, Contemporary Bayesian and Frequentist Statistical Research Methods for Natural Resource Scientists is an ideal text for natural resource students studying statistical research methods at the upper-undergraduate or graduate level and also serves as a valuable problem-solving guide for natural resource scientists across a broad range of disciplines, including biology, wildlife management, forestry management, fisheries management, and the environmental sciences.

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A. Gouveia Oliveira Biostatistics Decoded


Biostatistics Decoded  covered a large number of statistical methods that are mainly applied to clinical and epidemiological research, as well as a comprehensive discussion of study designs for observational research and clinical trials, two important concerns for the clinical researcher. In this second edition, new material is included covering statistical methods and study designs that are used to analyse research. Following the same methodology used in the first edition, the chapters are presented in two levels of detail, one for the reader who wishes only to understand the rationale behind each statistical method, and one for the reader who wishes to understand the computations Key features include: Extensive coverage of the design and analysis of experiments for basic science research Experimental designs are presented together with the statistical methods The rationale of all forms of ANOVA is explained with simple mathematics A comprehensive presentation of statistical tests for multiple comparisons Calculations for all statistical methods are illustrated with examples and explained step-by-step. This book presents biostatistical concepts and methods in a way that is accessible to anyone, regardless of his or her knowledge of mathematics. The topics selected for this book cover will meet the needs of clinical professionals to readers in basic science research.

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Bovas Abraham Statistical Methods for Forecasting


The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. «This book, it must be said, lives up to the words on its advertising cover: 'Bridging the gap between introductory, descriptive approaches and highly advanced theoretical treatises, it provides a practical, intermediate level discussion of a variety of forecasting tools, and explains how they relate to one another, both in theory and practice.' It does just that!» -Journal of the Royal Statistical Society «A well-written work that deals with statistical methods and models that can be used to produce short-term forecasts, this book has wide-ranging applications. It could be used in the context of a study of regression, forecasting, and time series analysis by PhD students; or to support a concentration in quantitative methods for MBA students; or as a work in applied statistics for advanced undergraduates.» -Choice Statistical Methods for Forecasting is a comprehensive, readable treatment of statistical methods and models used to produce short-term forecasts. The interconnections between the forecasting models and methods are thoroughly explained, and the gap between theory and practice is successfully bridged. Special topics are discussed, such as transfer function modeling; Kalman filtering; state space models; Bayesian forecasting; and methods for forecast evaluation, comparison, and control. The book provides time series, autocorrelation, and partial autocorrelation plots, as well as examples and exercises using real data. Statistical Methods for Forecasting serves as an outstanding textbook for advanced undergraduate and graduate courses in statistics, business, engineering, and the social sciences, as well as a working reference for professionals in business, industry, and government.

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