Описание: Volume I is devoted to continuous Gaussian linear mixed models and has nine chapters. The chapters are organized in four parts. The first part provides a review of the methods of linear regression. The second part provides an in-depth coverage of the two-level models, the simplest extensions of a linear regression model. The mixed-model foundation and the in-depth coverage of the mixed-model principles provided in volume I for continuous outcomes, make it straightforward to transition to generalized linear mixed models for noncontinuous outcomes described in volume II.
Описание: The numerical treatment of partial differential equations with meshfree discretization techniques has been a very active research area in recent years. Up to now, however, meshfree methods have been in an early experimental stage and were not competitive due to the lack of efficient iterative solvers and numerical quadrature. This volume now presents an efficient parallel implementation of a meshfree method, namely the partition of unity method (PUM). A general numerical integration scheme is presented for the efficient assembly of the stiffness matrix as well as an optimal multilevel solver for the arising linear system. Furthermore, detailed information on the parallel implementation of the method on distributed memory computers is provided and numerical results are presented in two and three space dimensions with linear, higher order and augmented approximation spaces with up to 42 million degrees of freedom.
Автор: Jeffrey S Simonoff Marc A Scott & Название: Sage Handbook of Multilevel Modeling ISBN: 0857025643 ISBN-13(EAN): 9780857025647 Издательство: Sage Publications Рейтинг: Цена: 14955 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: In this important new Handbook, the editors have gathered together a range of leading contributors to introduce the theory and practice of multilevel modeling. The Handbook establishes the connections in multilevel modeling, bringing together leading experts from around the world to provide a roadmap for applied researchers linking theory and practice, as well as a unique arsenal of state-of-the-art tools. It forges vital connections that cross traditional disciplinary divides and introduces best practice in the field. Part I establishes the framework for estimation and inference, including chapters dedicated to notation, model selection, fixed and random effects, and causal inference. Part II develops variations and extensions, such as nonlinear, semiparametric and latent class models. Part III includes discussion of missing data and robust methods, assessment of fit and software. Part IV consists of exemplary modeling and data analyses written by methodologists working in specific disciplines. Combining practical pieces with overviews of the field, this Handbook is essential reading for any student or researcher looking to apply multilevel techniques in their own research.
Автор: Leeuw Jan de, Meijer Erik Название: Handbook of Multilevel Analysis ISBN: 0387731830 ISBN-13(EAN): 9780387731834 Издательство: Springer Рейтинг: Цена: от 20376 р. Наличие на складе: Есть
Описание: Multilevel analysis is the statistical analysis of hierarchically and non-hierarchically nested data. The simplest example is clustered data, such as a sample of students clustered within schools. Multilevel data are especially prevalent in the social and behavioral sciences and in the bio-medical sciences. The models used for this type of data are linear and nonlinear regression models that account for observed and unobserved heterogeneity at the various levels in the data. This book presents the state of the art in multilevel analysis, with an emphasis on more advanced topics. These topics are discussed conceptually, analyzed mathematically, and illustrated by empirical examples. The authors of the chapters are the leading experts in the field.Given the omnipresence of multilevel data in the social, behavioral, and biomedical sciences, this book is useful for empirical researchers in these fields. Prior knowledge of multilevel analysis is not required, but a basic knowledge of regression analysis, (asymptotic) statistics, and matrix algebra is assumed.
Автор: Kreft I & de Leeuw J Название: Introducing Multilevel Modeling ISBN: 0761951407 ISBN-13(EAN): 9780761951407 Издательство: Sage Publications Рейтинг: Цена: 17864 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A practical guide to using multilevel models in social research. The approach is user-oriented, with formal mathematics and statistics being kept to a minimum. Worked examples, using real data sets, are analyzed with the help of the leading computer package for multilevel modelling.
Автор: Hox, Joop J. Название: Multilevel analysis ISBN: 1848728468 ISBN-13(EAN): 9781848728462 Издательство: Taylor&Francis Рейтинг: Цена: 3926 р. Наличие на складе: Поставка под заказ.
Описание: Helps readers apply multilevel techniques to their research. This book discusses basic models and examples, emphasising on understanding the methodological and statistical issues involved in using these models. It demonstrates the estimation and interpretation of multilevel models using realistic examples from various disciplines.
Автор: Vassilevski Название: Multilevel Block Factorization Preconditioners ISBN: 0387715630 ISBN-13(EAN): 9780387715636 Издательство: Springer Рейтинг: Цена: 12539 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This monograph is the first to provide a comprehensive, self-contained and rigorous presentation of some of the most powerful preconditioning methods for solving finite element equations in a common block-matrix factorization framework.
Автор: Goldstein, Harvey Название: Multilevel statistical models ISBN: 0340806559 ISBN-13(EAN): 9780340806555 Издательство: Wiley Рейтинг: Цена: 7392 р. Наличие на складе: Поставка под заказ.
Описание: Explaining important developments such as the use of Markov Chain Monte Carlo methods, bootstrapping and mulitvariate models, this book discusses key issues such as missing data, measurement errors and multivariate models. It uses real-life examples to illustrate the theoretical concepts.
Автор: Jos W. R. Twisk Название: Applied Multilevel Analysis ISBN: 0521614988 ISBN-13(EAN): 9780521614986 Издательство: Cambridge Academ Рейтинг: Цена: 4830 р. Наличие на складе: Поставка под заказ.
Описание: This is a practical introduction to multilevel analysis suitable for all those doing research. Most books on multilevel analysis are written by statisticians, and they focus on the mathematical background. These books are difficult for non-mathematical researchers. In contrast, this volume provides an accessible account on the application of multilevel analysis in research. It addresses the practical issues that confront those undertaking research and wanting to find the correct answers to research questions. This book is written for non-mathematical researchers and it explains when and how to use multilevel analysis. Many worked examples, with computer output, are given to illustrate and explain this subject. Datasets of the examples are available on the internet, so the reader can reanalyse the data. This approach will help to bridge the conceptual and communication gap that exists between those undertaking research and statisticians.
Автор: Gonzalez Название: Multilevel Converters for Industrial Applications ISBN: 1439895597 ISBN-13(EAN): 9781439895597 Издательство: Taylor&Francis Рейтинг: Цена: 23478 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Modern semiconductor devices have reached high current and voltage levels, and their power-handling limits can be extended if they are used in multilevel converter configurations. To create high-performance and reliable control designs, however, engineers need in-depth understanding of the characteristics and operation of these topologies. Multilevel Converters for Industrial Applications presents a thorough and comprehensive analysis of multilevel converters with a common DC voltage source. The book offers a novel perspective to help readers understand the principles of the operation of voltage-source multilevel converters as power processors, and their capabilities and limitations. The book begins with an overview of medium-voltage power converters and their applications. It then analyzes the topological characteristics of the diode-clamped multilevel converter, the flying capacitor multilevel converter, and the asymmetric cascaded multilevel converter. For each topology, the authors highlight particular control issues and design trade-offs. They also develop relevant modulation and control strategies. Numerous graphical representations aid in the analysis of the topologies and are useful for beginning the analysis of new multilevel converter topologies. The last two chapters of the book explore two case studies that analyze the behavior of the cascade asymmetric multilevel converter as a distribution static compensator and shunt active power filter, and the behavior of the diode-clamped topology configured as a back-to-back converter. These case studies demonstrate how to address the associated control problems with advanced control and modulation schemes. Examining recent advances, this book provides deep insight on the design of high-power multilevel converters and their applications. It is a valuable reference for anyone interested in medium-voltage power conversion, which is increasingly being used in industry and in renewable energy and distributed generation systems to improve efficiency and operation flexibility.
Автор: Scott L Thomas Ronald Heck & Название: Introduction to Multilevel Modeling Techniques ISBN: 1848725523 ISBN-13(EAN): 9781848725522 Издательство: Taylor&Francis Рейтинг: Цена: 7038 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Univariate and multivariate multilevel models are used to understand how to design studies and analyze data?in this comprehensive text distinguished by its variety of applications from the educational, behavioral, and social sciences. Basic and advanced models are developed from the?multilevel regression (MLM) and latent variable (SEM) traditions within one unified analytic framework for investigating hierarchical data. The authors provide examples using each modeling approach and also explore situations where alternative approaches may be more appropriate, given the research goals. Numerous examples and exercises allow readers to test their understanding of the techniques presented. Changes to the new edition include: -The use of Mplus 7.2 for running the analyses including the input and data files at www.routledge.com/9781848725522.? -Expanded discussion of MLM and SEM model-building that outlines the steps taken in the process, the relevant Mplus syntax, and tips on how to evaluate the models. -Expanded pedagogical program now with chapter objectives, boldfaced key terms, a glossary, and more tables and graphs to help students better understand key concepts and techniques. -Numerous, varied examples developed throughout which make this book appropriate for use in education, psychology, business, sociology, and the health sciences. -Expanded coverage of missing data problems in MLM using ML estimation and multiple imputation to provide currently-accepted solutions (Ch. 10). -New chapter on three-level univariate and multilevel multivariate MLM models provides greater options for investigating more complex theoretical relationships(Ch.4). -New chapter on MLM and SEM models with categorical outcomes facilitates the specification of multilevel models with observed and latent outcomes (Ch.8). -New chapter on multilevel and longitudinal mixture models provides readers with options for identifying emergent groups in hierarchical data (Ch.9). -New chapter on the utilization of sample weights, power analysis, and missing data provides guidance on technical issues of increasing concern for research publication (Ch.10). Ideal as a text for graduate courses on multilevel, longitudinal, latent variable modeling, multivariate statistics, or advanced quantitative techniques taught in psychology, business, education, health, and sociology, this book’s practical approach also appeals to researchers. Recommended prerequisites are introductory univariate and multivariate statistics.
Автор: Heck Название: An Introduction to Multilevel Modeling Techniques ISBN: 1848725515 ISBN-13(EAN): 9781848725515 Издательство: Taylor&Francis Рейтинг: Цена: 15593 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Univariate and multivariate multilevel models are used to understand how to design studies and analyze data?in this comprehensive text distinguished by its variety of applications from the educational, behavioral, and social sciences. Basic and advanced models are developed from the?multilevel regression (MLM) and latent variable (SEM) traditions within one unified analytic framework for investigating hierarchical data. The authors provide examples using each modeling approach and also explore situations where alternative approaches may be more appropriate, given the research goals. Numerous examples and exercises allow readers to test their understanding of the techniques presented. Changes to the new edition include: -The use of Mplus 7.2 for running the analyses including the input and data files at www.routledge.com/9781848725522.? -Expanded discussion of MLM and SEM model-building that outlines the steps taken in the process, the relevant Mplus syntax, and tips on how to evaluate the models. -Expanded pedagogical program now with chapter objectives, boldfaced key terms, a glossary, and more tables and graphs to help students better understand key concepts and techniques. -Numerous, varied examples developed throughout which make this book appropriate for use in education, psychology, business, sociology, and the health sciences. -Expanded coverage of missing data problems in MLM using ML estimation and multiple imputation to provide currently-accepted solutions (Ch. 10). -New chapter on three-level univariate and multilevel multivariate MLM models provides greater options for investigating more complex theoretical relationships(Ch.4). -New chapter on MLM and SEM models with categorical outcomes facilitates the specification of multilevel models with observed and latent outcomes (Ch.8). -New chapter on multilevel and longitudinal mixture models provides readers with options for identifying emergent groups in hierarchical data (Ch.9). -New chapter on the utilization of sample weights, power analysis, and missing data provides guidance on technical issues of increasing concern for research publication (Ch.10). Ideal as a text for graduate courses on multilevel, longitudinal, latent variable modeling, multivariate statistics, or advanced quantitative techniques taught in psychology, business, education, health, and sociology, this book’s practical approach also appeals to researchers. Recommended prerequisites are introductory univariate and multivariate statistics.
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