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Multilevel Statistical Models, Giorgos Michel


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Цена: 217350.00T
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Автор: Giorgos Michel
Название:  Multilevel Statistical Models
ISBN: 9781681174464
Издательство: Gazelle Book Services
Классификация:




ISBN-10: 1681174464
Обложка/Формат: Hardback
Страницы: 298
Вес: 0.00 кг.
Дата издания: 01.01.2017
Серия: Mathematics
Язык: English
Размер: 229 x 152
Читательская аудитория: Postgraduate, research & scholarly
Ключевые слова: Mathematics
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Поставляется из: Англии
Описание: Through the social, medical and other sciences the importance of understanding complex hierarchical data structures is well understood. Multilevel modelling is now the accepted statistical technique for handling such data and is widely available in computer software packages. A thorough understanding of these techniques is therefore important for all those working in these areas. Multilevel models (also hierarchical linear models, nested models, mixed models, random coefficient, random-effects models, random parameter models, or split-plot designs) are statistical models of parameters that vary at more than one level. An example could be a model of student performance that contains measures for individual students as well as measures for classrooms within which the students are grouped. These models can be seen as generalizations of linear models (in particular, linear regression), although they can also extend to non-linear models. These models became much more popular after sufficient computing power and software became available. Multilevel models are particularly appropriate for research designs where data for participants are organized at more than one level (i.e., nested data). Multilevel models can be used on data with many levels, although 2-level models are the most common and the rest of this article deals only with these. The dependent variable must be examined at the lowest level of analysis. The book Multilevel Statistical Models brings these techniques together, starting from basic ideas and illustrating how more complex models are derived. This book is a comprehensive tool for postgraduate courses. This book will be beneficial for applied statisticians in the social sciences, economics, biological and medical disciplines.

Multilevel Modeling in Plain Language

Автор: Karen Robson and David Pevalin
Название: Multilevel Modeling in Plain Language
ISBN: 0857029150 ISBN-13(EAN): 9780857029157
Издательство: Sage Publications
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Цена: 106650.00 T
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Описание: With a real focus on the practical, this book provides students with a step-by-step approach, plenty of real-life examples, and downloadable data and exercises on the accompanying study website to help take the fear and intimidation out of multilevel modeling

Multilevel Modeling in Plain Language

Автор: Robson Karen
Название: Multilevel Modeling in Plain Language
ISBN: 0857029169 ISBN-13(EAN): 9780857029164
Издательство: Sage Publications
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Цена: 32730.00 T
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Описание: With a real focus on the practical, this book provides students with a step-by-step approach, plenty of real-life examples, and downloadable data and exercises on the accompanying study website to help take the fear and intimidation out of multilevel modeling

Parallel Multilevel Methods

Автор: Gerhard Zumbusch
Название: Parallel Multilevel Methods
ISBN: 3519004518 ISBN-13(EAN): 9783519004516
Издательство: Springer
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Цена: 35390.00 T
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Описание: Numerical simulation promises new insight in science and engineering. In ad- dition to the traditional ways to perform research in science, that is laboratory experiments and theoretical work, a third way is being established: numerical simulation. It is based on both mathematical models and experiments con- ducted on a computer. The discipline of scientific computing combines all aspects of numerical simulation. The typical approach in scientific computing includes modelling, numerics and simulation, see Figure l. Quite a lot of phenomena in science and engineering can be modelled by partial differential equations (PDEs). In order to produce accurate results, complex models and high resolution simulations are needed. While it is easy to increase the precision of a simulation, the computational cost of doing so is often prohibitive. Highly efficient simulation methods are needed to overcome this problem. This includes three building blocks for computational efficiency, discretisation, solver and computer. Adaptive mesh refinement, high order and sparse grid methods lead to discretisations of partial differential equations with a low number of degrees of freedom. Multilevel iterative solvers decrease the amount of work per degree of freedom for the solution of discretised equation systems. Massively parallel computers increase the computational power available for a single simulation.

Data analysis using regression and multilevel/hierarchical models

Автор: Gelman
Название: Data analysis using regression and multilevel/hierarchical models
ISBN: 052168689X ISBN-13(EAN): 9780521686891
Издательство: Cambridge Academ
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Цена: 57030.00 T
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Описание: Data Analysis Using Regression and Multilevel/Hierarchical Models, first published in 2007, is a comprehensive manual for the applied researcher who wants to perform data analysis using linear and nonlinear regression and multilevel models. It introduces and demonstrates a variety of models and instructs the reader in how to fit these models using freely available software packages.

Multilevel Analysis

Автор: Snijders Tom
Название: Multilevel Analysis
ISBN: 184920201X ISBN-13(EAN): 9781849202015
Издательство: Sage Publications
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Цена: 58080.00 T
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Описание: The classic text in multilevel analysis, dealing with everything you need to know, has been hugely revised and added to and is supported by all the software. A must-have for modellers.


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