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Mixed Models
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 m...
Advanced Statistics with Applications in R
Advanced Statistics with Applications in R fills the gap between several excellent theoretical statistics textbooks and many applied statistics books where teaching reduces to using existing packages. This book looks at what is under the hood. Many statistics issues including the recent crisis with p-value are caused by misunderstanding of statistical concepts due to poor theoretical background of practitioners and applied statisticians. This book is the product of a forty-year experience in teaching of probability and statistics and their applications for solving real-life problems. There are more than 442 examples in the book: basically every probability or statistics concept is illustrate...
Mixed Models
A rigorous, self-contained examination of mixed model theory and application Mixed modeling is one of the most promising and exciting areas of statistical analysis, enabling the analysis of nontraditional, clustered data that may come in the form of shapes or images. This book provides in-depth mathematical coverage of mixed models’ statistical properties and numerical algorithms, as well as applications such as the analysis of tumor regrowth, shape, and image. Paying special attention to algorithms and their implementations, the book discusses: Modeling of complex clustered or longitudinal data Modeling data with multiple sources of variation Modeling biological variety and heterogeneity ...
M-statistics
M-STATISTICS A comprehensive resource providing new statistical methodologies and demonstrating how new approaches work for applications M-statistics introduces a new approach to statistical inference, redesigning the fundamentals of statistics, and improving on the classical methods we already use. This book targets exact optimal statistical inference for a small sample under one methodological umbrella. Two competing approaches are offered: maximum concentration (MC) and mode (MO) statistics combined under one methodological umbrella, which is why the symbolic equation M=MC+MO. M-statistics defines an estimator as the limit point of the MC or MO exact optimal confidence interval when the c...
Modelling Longitudinal and Spatially Correlated Data
Correlated data arise in numerous contexts across a wide spectrum of subject-matter disciplines. Modeling such data present special challenges and opportunities that have received increasing scrutiny by the statistical community in recent years. In October 1996 a group of 210 statisticians and other scientists assembled on the small island of Nantucket, U. S. A. , to present and discuss new developments relating to Modelling Longitudinal and Spatially Correlated Data: Methods, Applications, and Future Direc tions. Its purpose was to provide a cross-disciplinary forum to explore the commonalities and meaningful differences in the source and treatment of such data. This volume is a compilation...
Computational Science and Its Applications - ICCSA 2004
The natural mission of Computational Science is to tackle all sorts of human problems and to work out intelligent automata aimed at alleviating the b- den of working out suitable tools for solving complex problems. For this reason ComputationalScience,thoughoriginatingfromtheneedtosolvethemostch- lenging problems in science and engineering (computational science is the key player in the ?ght to gain fundamental advances in astronomy, biology, che- stry, environmental science, physics and several other scienti?c and engineering disciplines) is increasingly turning its attention to all ?elds of human activity. In all activities, in fact, intensive computation, information handling, kn- ledge s...
The Street
Vacant lots. Historic buildings overgrown with weeds. Walls and alleyways covered with graffiti. These are sights associated with countless inner-city neighborhoods in America, and yet many viewers have trouble getting beyond the surface of such images, whether they are denigrating them as signs of a dangerous ghetto or romanticizing them as traits of a beautiful ruined landscape. The Street: A Field Guide to Inequality provides readers with the critical tools they need to go beyond such superficial interpretations of urban decay. Using MacArthur fellow Camilo José Vergara’s intimate street photographs of Camden, New Jersey as reference points, the essays in this collection analyze these ...
Handbook Of Immunological Properties Of Engineered Nanomaterials (Second Edition) (In 3 Volumes)
This unique book provides comprehensive overview of the field of immunology related to engineered nanomaterials used for biomedical applications. It contains literature review, case studies and protocols. The book can serve as a source of information about nanoimmunotoxicology for both junior scientists and experts in the field. The authors have more than 10 years of experience with preclinical characterization of engineered nanomaterials used for medical applications, and they share their experience with the readers. In addition, the international team of experts in the field provides the opinion and share the expertise on individual topics related to nanoparticle physicochemical characteri...
Industrial Data Analytics for Diagnosis and Prognosis
Discover data analytics methodologies for the diagnosis and prognosis of industrial systems under a unified random effects model In Industrial Data Analytics for Diagnosis and Prognosis - A Random Effects Modelling Approach, distinguished engineers Shiyu Zhou and Yong Chen deliver a rigorous and practical introduction to the random effects modeling approach for industrial system diagnosis and prognosis. In the book’s two parts, general statistical concepts and useful theory are described and explained, as are industrial diagnosis and prognosis methods. The accomplished authors describe and model fixed effects, random effects, and variation in univariate and multivariate datasets and cover ...
Negotiating Structural Vulnerability in Cancer Control
What can case studies about the lived experiences of cancer contribute to an interest in the concept of structural vulnerability? And can a consideration of structural vulnerability enhance applied anthropological work in cancer prevention and control? To answer these questions the contributors in this volume explore what it means to be structurally vulnerable; how structural vulnerabilities intersect with cancer risk, diagnosis, care seeking, caregiving, clinical-trial participation, and survivorship; and how differing local, national, and global political contexts and histories inform vulnerability. These case studies illustrate how quotidian experiences of structural vulnerability influence and are altered by a cancer diagnosis at various points in the continuum of care. In examining cancer as a set of diseases and biosocial phenomena, the contributors extend structural vulnerability beyond its original conceptualization to encompass spatiality, temporality, and biosocial shifts in both individual and institutional arrangements.
