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Praise for the First Edition " . . . the book is a valuable addition to the literature in thefield, serving as a much-needed guide for both clinicians andadvanced students."--Zentralblatt MATH A new edition of the cutting-edge guide to diagnostic tests inmedical research In recent years, a considerable amount of research has focusedon evolving methods for designing and analyzing diagnostic accuracystudies. Statistical Methods in Diagnostic Medicine, Second Editioncontinues to provide a comprehensive approach to the topic, guidingreaders through the necessary practices for understanding thesestudies and generalizing the results to patient populations. Following a basic introduction to measuring test accuracy andstudy design, the authors successfully define various measures ofdiagnostic accuracy, describe strategies for designing diagnosticaccuracy studies, and present key statistical methods forestimating and comparing test accuracy. Topics new to the SecondEdition include: * Methods for tests designed to detect and locate lesions * Recommendations for covariate-adjustment * Methods for estimating and comparing predictive values andsample size calculations * Correcting techniques for verification and imperfect standardbiases * Sample size calculation for multiple reader studies when pilotdata are available * Updated meta-analysis methods, now incorporating randomeffects Three case studies thoroughly showcase some of the questions andstatistical issues that arise in diagnostic medicine, with allassociated data provided in detailed appendices. A related web sitefeatures Fortran, SAS®, and R software packages so thatreaders can conduct their own analyses. Statistical Methods in Diagnostic Medicine, Second Edition is anexcellent supplement for biostatistics courses at the graduatelevel. It also serves as a valuable reference for clinicians andresearchers working in the fields of medicine, epidemiology, andbiostatistics.

Statistical Learning with Sparsity

This book focuses on the spatial distribution of landslide hazards of the Darjeeling Himalayas. Knowledge driven methods and statistical techniques such as frequency ratio model (FRM), information value model (IVM), logistic regression model (LRM), index overlay model (IOM), certainty factor model (CFM), analytical hierarchy process (AHP), artificial neural network model (ANN), and fuzzy logic have been adopted to identify landslide susceptibility. In addition, a comparison between various statistical models were made using success rate cure (SRC) and it was found that artificial neural network model (ANN), certainty factor model (CFM) and frequency ratio based fuzzy logic approach are the most reliable statistical techniques in the assessment and prediction of landslide susceptibility in the Darjeeling Himalayas. The study identified very high, high, moderate, low and very low landslide susceptibility locations to take site-specific management options as well as to ensure developmental activities in theDarjeeling Himalayas. Particular attention is given to the assessment of various geomorphic, geotectonic and geohydrologic attributes that help to understand the role of different factors and corresponding classes in landslides, to apply different models, and to monitor and predict landslides. The use of various statistical and physical models to estimate landslide susceptibility is also discussed. The causes, mechanisms and types of landslides and their destructive character are elaborated in the book. Researchers interested in applying statistical tools for hazard zonation purposes will find the book appealing.

Take an exhilarating journey through the modern revolution in statistics with two of the ringleaders.

This work is an overview of statistical inference in stationary, discrete time stochastic processes. Results in the last fifteen years, particularly on non-Gaussian sequences and semi-parametric and non-parametric analysis have been reviewed. The first chapter gives a background of results on martingales and strong mixing sequences, which enable us to generate various classes of CAN estimators in the case of dependent observations. Topics discussed include inference in Markov chains and extension of Markov chains such as Raftery's Mixture Transition Density model and Hidden Markov chains and extensions of ARMA models with a Binomial, Poisson, Geometric, Exponential, Gamma, Weibull, Lognormal, Inverse Gaussian and Cauchy as stationary distributions. It further discusses applications of semi-parametric methods of estimation such as conditional least squares and estimating functions in stochastic models. Construction of confidence intervals based on estimating functions is discussed in some detail. Kernel based estimation of joint density and conditional expectation are also discussed. Bootstrap and other resampling procedures for dependent sequences such as Markov chains, Markov sequences, linear auto-regressive moving average sequences, block based bootstrap for stationary sequences and other block based procedures are also discussed in some detail. This work can be useful for researchers interested in knowing developments in inference in discrete time stochastic processes. It can be used as a material for advanced level research students.

Pages: 236 Soft cover Publisher: Sage English In an increasingly data-centric world, we all need to know how to read and interpret statistics. But where do w...

This book introduces and discusses the analysis of interacting many-body complex systems exhibiting spontaneous synchronization from the perspective of nonequilibrium statistical physics. While such systems have been mostly studied using dynamical system theory, the book underlines the usefulness of the statistical physics approach to obtain insightful results in a number of representative dynamical settings. Although it is intractable to follow the dynamics of a particular initial condition, statistical physics allows to derive exact analytical results in the limit of an infinite number of interacting units. Chapter one discusses dynamical characterization of individual units of synchronizing systems as well as of their interaction and summarizes the relevant tools of statistical physics. The latter are then used in chapters two and three to discuss respectively synchronizing systems with either a first- or a second-order evolution in time. This book provides a timely introduction to the subject and is meant for the uninitiated as well as for experienced researchers working in areas of nonlinear dynamics and chaos, statistical physics, and complex systems.

Penguin presents the unabridged, downloadable, audiobook edition of a Field Guide to Lies by David Levitin, read by Dan Piraro.The bestselling author of The ...

This statistics textbook, with particular emphasis on radiation protection and dosimetry, deals with statistical solutions to problems inherent in health physics measurements and decision making. The authors begin with a description of our current understanding of the statistical nature of physical processes at the atomic level, including radioactive decay and interactions of radiation with matter. Examples are taken from problems encountered in health physics, and the material is presented such that health physicists and most other nuclear professionals will more readily understand the application of statistical principles in the familiar context of the examples. Problems are presented at the end of each chapter, with solutions to selected problems provided online. In addition, numerous worked examples are included throughout the text.

Essential Statistics for Data Science: A Concise Crash Course is for students entering a serious graduate program in data science without knowing enough stat...

Amstat News asked three review editors to rate their topfive favorite books in the September 2003 issue. StatisticalMethods for Reliability Data was among those chosen. Bringing statistical methods for reliability testing in linewith the computer age This volume presents state-of-the-art,computer-based statistical methods for reliability data analysisand test planning for industrial products. Statistical Methodsfor Reliability Data updates and improves establishedtechniques as it demonstrates how to apply the new graphical,numerical, or simulation-based methods to a broad range of modelsencountered in reliability data analysis. It includes methods forplanning reliability studies and analyzing degradation data,simulation methods used to complement large-sample asymptotictheory, general likelihood-based methods of handling arbitrarilycensored data and truncated data, and more. In this book, engineersand statisticians in industry and academia will find: * A wealth of information and procedures developed to giveproducts a competitive edge * Simple examples of data analysis computed with the S-PLUSsystem-for which a suite of functions and commands is availableover the Internet * End-of-chapter, real-data exercise sets * Hundreds of computer graphics illustrating data, results ofanalyses, and technical concepts An essential resource for practitioners involved in productreliability and design decisions, Statistical Methods forReliability Data is also an excellent textbook for on-the-jobtraining courses, and for university courses on applied reliabilitydata analysis at the graduate level. An Instructor's Manual presenting detailed solutions to all theproblems in the book is available upon requestfrom the Wileyeditorial department.

This updated and reorganized Third Edition of this textbook takes a workbook-style approach that encourages an active approach to learning statistics. Carefu...

This book focuses on experimental research in two disciplines that have a lot of common ground in terms of theory, experimental designs used, and methods for the analysis of experimental research data: education and psychology. Although the methods covered in this book are also frequently used in many other disciplines, including sociology and medicine, the examples in this book come from contemporary research topics in education and psychology. Various statistical packages, commercial and zero-cost Open Source ones, are used. The goal of this book is neither to cover all possible statistical methods out there nor to focus on a particular statistical software package. There are many excellent statistics textbooks on the market that present both basic and advanced concepts at an introductory level and/or provide a very detailed overview of options in a particular statistical software programme. This is not yet another book in that genre.   Core theme of this book is a heuristic called the question-design-analysis bridge: there is a bridge connecting research questions and hypotheses, experimental design and sampling procedures, and common statistical methods in that context. Each statistical method is discussed in a concrete context of a set of research question with directed (one-sided) or undirected (two-sided) hypotheses and an experimental setup in line with these questions and hypotheses. Therefore, the titles of the chapters in this book do not include any names of statistical methods such as ‘analysis of variance’ or ‘analysis of covariance’. In a total of seventeen chapters, this book covers a wide range of topics of research questions that call for experimental designs and statistical methods, fairly basic or more advanced.      

Credit scoring models are the basis for financial institutions like retail and consumer credit banks. The purpose of the models is to evaluate the likelihood...

As an area of statistical application, environmental epidemiology and more speci cally, the estimation of health risk associated with the exposure to - vironmental agents, has led to the development of several statistical methods and software that can then be applied to other scienti c areas. The stat- tical analyses aimed at addressing questions in environmental epidemiology have the following characteristics. Often the signal-to-noise ratio in the data is low and the targets of inference are inherently small risks. These constraints typically lead to the development and use of more sophisticated (and pot- tially less transparent) statistical models and the integration of large hi- dimensional databases. New technologies and the widespread availability of powerful computing are also adding to the complexities of scienti c inves- gation by allowing researchers to t large numbers of models and search over many sets of variables. As the number of variables measured increases, so do the degrees of freedom for in uencing the association between a risk factor and an outcome of interest. We have written this book, in part, to describe our experiences developing and applying statistical methods for the estimation for air pollution health e ects. Our experience has convinced us that the application of modern s- tistical methodology in a reproducible manner can bring to bear subst- tial bene ts to policy-makers and scientists in this area. We believe that the methods described in this book are applicable to other areas of environmental epidemiology, particularly those areas involving spatial{temporal exposures.

This comprehensive Second Edition offers readers a complete guide to carrying out research projects involving structural equation modeling (SEM). Updated to ...

Statistical pattern recognition relates to the use of statisticaltechniques for analysing data measurements in order to extractinformation and make justified decisions. It is a very activearea of study and research, which has seen many advances in recentyears. Applications such as data mining, web searching, multimediadata retrieval, face recognition, and cursive handwritingrecognition, all require robust and efficient pattern recognitiontechniques. This third edition provides an introduction to statisticalpattern theory and techniques, with material drawn from a widerange of fields, including the areas of engineering, statistics,computer science and the social sciences. The book has been updatedto cover new methods and applications, and includes a wide range oftechniques such as Bayesian methods, neural networks, supportvector machines, feature selection and feature reductiontechniques.Technical descriptions and motivations are provided, andthe techniques are illustrated using real examples. Statistical Pattern Recognition, 3rdEdition: * Provides a self-contained introduction to statistical patternrecognition. * Includes new material presenting the analysis of complexnetworks. * Introduces readers to methods for Bayesian densityestimation. * Presents descriptions of new applications in biometrics,security, finance and condition monitoring. * Provides descriptions and guidance for implementing techniques,which will be invaluable to software engineers and developersseeking to develop real applications * Describes mathematically the range of statistical patternrecognition techniques. * Presents a variety of exercises including more extensivecomputer projects. The in-depth technical descriptions make the book suitable forsenior undergraduate and graduate students in statistics, computerscience and engineering. Statistical PatternRecognition is also an excellent reference source for technicalprofessionals. Chapters have been arranged to facilitateimplementation of the techniques by software engineers anddevelopers in non-statistical engineering fields. www.wiley.com/go/statistical_pattern_recognition

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This book presents the methodology and applications of a range of important topics in statistics, and is designed for graduate students in Statistics and Biostatistics and for medical researchers. Illustrations and more than ninety exercises with solutions are presented. They are constructed from the research findings of the medical journals, summary reports of the Centre for Disease Control (CDC) and the World Health Organization (WHO), and practical situations. The illustrations and exercises are related to topics such as immunization, obesity, hypertension, lipid levels, diet and exercise, harmful effects of smoking and air pollution, and the benefits of gluten free diet. This book can be recommended for a one or two semester graduate level course for students studying Statistics, Biostatistics, Epidemiology and Health Sciences. It will also be useful as a companion for medical researchers and research oriented physicians.

A wonderfully written and entertaining book which places Britain under the microscope and asks who we are today and how we've changed as a nation.'Entertaini...