Statistical Meta Analysis With Applications Wiley Series In Probability And Statistics
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Statistical Meta Analysis With Applications Wiley Series In Probability And Statistics
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Author : Guido Knapp
language : en
Publisher:
Release Date : 2008
Statistical Meta Analysis With Applications Wiley Series In Probability And Statistics written by Guido Knapp and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with categories.
Statistical Meta Analysis With Applications
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Author : Joachim Hartung
language : en
Publisher: John Wiley & Sons
Release Date : 2011-09-20
Statistical Meta Analysis With Applications written by Joachim Hartung 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 Medical categories.
An accessible introduction to performing meta-analysis across various areas of research The practice of meta-analysis allows researchers to obtain findings from various studies and compile them to verify and form one overall conclusion. Statistical Meta-Analysis with Applications presents the necessary statistical methodologies that allow readers to tackle the four main stages of meta-analysis: problem formulation, data collection, data evaluation, and data analysis and interpretation. Combining the authors' expertise on the topic with a wealth of up-to-date information, this book successfully introduces the essential statistical practices for making thorough and accurate discoveries across a wide array of diverse fields, such as business, public health, biostatistics, and environmental studies. Two main types of statistical analysis serve as the foundation of the methods and techniques: combining tests of effect size and combining estimates of effect size. Additional topics covered include: Meta-analysis regression procedures Multiple-endpoint and multiple-treatment studies The Bayesian approach to meta-analysis Publication bias Vote counting procedures Methods for combining individual tests and combining individual estimates Using meta-analysis to analyze binary and ordinal categorical data Numerous worked-out examples in each chapter provide the reader with a step-by-step understanding of the presented methods. All exercises can be computed using the R and SAS software packages, which are both available via the book's related Web site. Extensive references are also included, outlining additional sources for further study. Requiring only a working knowledge of statistics, Statistical Meta-Analysis with Applications is a valuable supplement for courses in biostatistics, business, public health, and social research at the upper-undergraduate and graduate levels. It is also an excellent reference for applied statisticians working in industry, academia, and government.
Statistical Methods In Diagnostic Medicine
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Author : Xiao-Hua Zhou
language : en
Publisher: John Wiley & Sons
Release Date : 2009-09-25
Statistical Methods In Diagnostic Medicine written by Xiao-Hua Zhou 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 2009-09-25 with Mathematics categories.
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.
Meta Analysis
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Author : Mike W.-L. Cheung
language : en
Publisher: John Wiley & Sons
Release Date : 2015-05-06
Meta Analysis written by Mike W.-L. Cheung 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 2015-05-06 with Mathematics categories.
Presents a novel approach to conducting meta-analysis using structural equation modeling. Structural equation modeling (SEM) and meta-analysis are two powerful statistical methods in the educational, social, behavioral, and medical sciences. They are often treated as two unrelated topics in the literature. This book presents a unified framework on analyzing meta-analytic data within the SEM framework, and illustrates how to conduct meta-analysis using the metaSEM package in the R statistical environment. Meta-Analysis: A Structural Equation Modeling Approach begins by introducing the importance of SEM and meta-analysis in answering research questions. Key ideas in meta-analysis and SEM are briefly reviewed, and various meta-analytic models are then introduced and linked to the SEM framework. Fixed-, random-, and mixed-effects models in univariate and multivariate meta-analyses, three-level meta-analysis, and meta-analytic structural equation modeling, are introduced. Advanced topics, such as using restricted maximum likelihood estimation method and handling missing covariates, are also covered. Readers will learn a single framework to apply both meta-analysis and SEM. Examples in R and in Mplus are included. This book will be a valuable resource for statistical and academic researchers and graduate students carrying out meta-analyses, and will also be useful to researchers and statisticians using SEM in biostatistics. Basic knowledge of either SEM or meta-analysis will be helpful in understanding the materials in this book.
A Practical Guide To Data Mining For Business And Industry
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Author : Andrea Ahlemeyer-Stubbe
language : en
Publisher: John Wiley & Sons
Release Date : 2014-03-31
A Practical Guide To Data Mining For Business And Industry written by Andrea Ahlemeyer-Stubbe 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 2014-03-31 with Mathematics categories.
Data mining is well on its way to becoming a recognized discipline in the overlapping areas of IT, statistics, machine learning, and AI. Practical Data Mining for Business presents a user-friendly approach to data mining methods, covering the typical uses to which it is applied. The methodology is complemented by case studies to create a versatile reference book, allowing readers to look for specific methods as well as for specific applications. The book is formatted to allow statisticians, computer scientists, and economists to cross-reference from a particular application or method to sectors of interest.
New Frontiers In Statistics And Data Science
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Author : Lígia Henriques-Rodrigues
language : en
Publisher: Springer Nature
Release Date : 2025-01-10
New Frontiers In Statistics And Data Science written by Lígia Henriques-Rodrigues and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-10 with Mathematics categories.
This volume showcases a collection of thirty-two peer-reviewed articles presented at the XXVI Congress of the Portuguese Statistical Society (2023). It covers a wide range of cutting-edge topics in both theoretical and applied statistics. Each contribution highlights the latest advancements and research in the field, offering valuable insights and innovative methodologies for researchers and practitioners alike. Readers with a background in mathematics and statistics will find it particularly beneficial, while researchers from various scientific disciplines can explore numerous robust applications.
Novelty Information And Surprise
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Author : Günther Palm
language : en
Publisher: Springer Nature
Release Date : 2023-01-02
Novelty Information And Surprise written by Günther Palm and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-02 with Mathematics categories.
This revised edition offers an approach to information theory that is more general than the classical approach of Shannon. Classically, information is defined for an alphabet of symbols or for a set of mutually exclusive propositions (a partition of the probability space Ω) with corresponding probabilities adding up to 1. The new definition is given for an arbitrary cover of Ω, i.e. for a set of possibly overlapping propositions. The generalized information concept is called novelty and it is accompanied by two concepts derived from it, designated as information and surprise, which describe "opposite" versions of novelty, information being related more to classical information theory and surprise being related more to the classical concept of statistical significance. In the discussion of these three concepts and their interrelations several properties or classes of covers are defined, which turn out to be lattices. The book also presents applications of these concepts, mostly in statistics and in neuroscience.
Mixed Models
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Author : Eugene Demidenko
language : en
Publisher: John Wiley & Sons
Release Date : 2013-08-05
Mixed Models written by Eugene Demidenko 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 2013-08-05 with Mathematics categories.
Praise for the First Edition “This book will serve to greatly complement the growing number of texts dealing with mixed models, and I highly recommend including it in one’s personal library.” —Journal of the American Statistical Association Mixed modeling is a crucial area of statistics, enabling the analysis of clustered and longitudinal data. Mixed Models: Theory and Applications with R, Second Edition fills a gap in existing literature between mathematical and applied statistical books by presenting a powerful examination of mixed model theory and application with special attention given to the implementation in R. The new edition provides in-depth mathematical coverage of mixed models’ statistical properties and numerical algorithms, as well as nontraditional applications, such as regrowth curves, shapes, and images. The book features the latest topics in statistics including modeling of complex clustered or longitudinal data, modeling data with multiple sources of variation, modeling biological variety and heterogeneity, Healthy Akaike Information Criterion (HAIC), parameter multidimensionality, and statistics of image processing. Mixed Models: Theory and Applications with R, Second Edition features unique applications of mixed model methodology, as well as: Comprehensive theoretical discussions illustrated by examples and figures Over 300 exercises, end-of-section problems, updated data sets, and R subroutines Problems and extended projects requiring simulations in R intended to reinforce material Summaries of major results and general points of discussion at the end of each chapter Open problems in mixed modeling methodology, which can be used as the basis for research or PhD dissertations Ideal for graduate-level courses in mixed statistical modeling, the book is also an excellent reference for professionals in a range of fields, including cancer research, computer science, and engineering.
Network Meta Analysis For Decision Making
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Author : Sofia Dias
language : en
Publisher: John Wiley & Sons
Release Date : 2018-03-19
Network Meta Analysis For Decision Making written by Sofia Dias 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 2018-03-19 with Mathematics categories.
A practical guide to network meta-analysis with examples and code In the evaluation of healthcare, rigorous methods of quantitative assessment are necessary to establish which interventions are effective and cost-effective. Often a single study will not provide the answers and it is desirable to synthesise evidence from multiple sources, usually randomised controlled trials. This book takes an approach to evidence synthesis that is specifically intended for decision making when there are two or more treatment alternatives being evaluated, and assumes that the purpose of every synthesis is to answer the question "for this pre-identified population of patients, which treatment is 'best'?" A comprehensive, coherent framework for network meta-analysis (mixed treatment comparisons) is adopted and estimated using Bayesian Markov Chain Monte Carlo methods implemented in the freely available software WinBUGS. Each chapter contains worked examples, exercises, solutions and code that may be adapted by readers to apply to their own analyses. This book can be used as an introduction to evidence synthesis and network meta-analysis, its key properties and policy implications. Examples and advanced methods are also presented for the more experienced reader. Methods used throughout this book can be applied consistently: model critique and checking for evidence consistency are emphasised. Methods are based on technical support documents produced for NICE Decision Support Unit, which support the NICE Methods of Technology Appraisal. Code presented is also the basis for the code used by the ISPOR Task Force on Indirect Comparisons. Includes extensive carefully worked examples, with thorough explanations of how to set out data for use in WinBUGS and how to interpret the output. Network Meta-Analysis for Decision Making will be of interest to decision makers, medical statisticians, health economists, and anyone involved in Health Technology Assessment including the pharmaceutical industry.