mixed effects models in s and s plus statistics and computing

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Mixed Effects Models In S And S Plus

Author : José C. Pinheiro
ISBN : 9781441903174
Genre : Computers
File Size : 77. 6 MB
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R, linear models, random, fixed, data, analysis, fit.

Mixed Effects Models In S And S Plus

Author : José C. Pinheiro
ISBN : 9781441903181
Genre : Computers
File Size : 34. 94 MB
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An overview of the theory and application of linear and nonlinear mixed-effects models in the analysis of grouped data, such as longitudinal data, repeated measures, and multilevel data. The authors present a unified model-building strategy for both models and apply this to the analysis of over 20 real datasets from a wide variety of areas, including pharmacokinetics, agriculture, and manufacturing. Much emphasis is placed on the use of graphical displays at the various phases of the model-building process, starting with exploratory plots of the data and concluding with diagnostic plots to assess the adequacy of a fitted model. The NLME library for analyzing mixed-effects models in S and S-PLUS, developed by the authors, provides the underlying software for implementing the methods presented. This balanced mix of real data examples, modeling software, and theory makes the book a useful reference for practitioners who use, or intend to use, mixed-effects models in their data analyses. It can also be used as a text for a one-semester graduate-level applied course.

The Sage Handbook Of Multilevel Modeling

Author : Marc A. Scott
ISBN : 9781446265970
Genre : Reference
File Size : 48. 73 MB
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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.

Complex Models And Computational Methods In Statistics

Author : Matteo Grigoletto
ISBN : 9788847028715
Genre : Mathematics
File Size : 62. 91 MB
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The use of computational methods in statistics to face complex problems and highly dimensional data, as well as the widespread availability of computer technology, is no news. The range of applications, instead, is unprecedented. As often occurs, new and complex data types require new strategies, demanding for the development of novel statistical methods and suggesting stimulating mathematical problems. This book is addressed to researchers working at the forefront of the statistical analysis of complex systems and using computationally intensive statistical methods.

Campbell Biologie

Author : Neil A. Campbell
ISBN : 3868942599
Genre :
File Size : 82. 31 MB
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Modern Applied Statistics With S

Author : W.N. Venables
ISBN : 9780387217062
Genre : Mathematics
File Size : 72. 25 MB
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A guide to using S environments to perform statistical analyses providing both an introduction to the use of S and a course in modern statistical methods. The emphasis is on presenting practical problems and full analyses of real data sets.

Modelling Nutrient Digestion And Utilisation In Farm Animals

Author : D. Sauvant
ISBN : 9789086867127
Genre : Science
File Size : 44. 24 MB
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For more than 30 years, modelling has been an important method for integrating, in a flexible, comprehensive and widely applicable way, basic knowledge and biological concepts on digestion and metabolism in farm animals. The purpose of this book is to present the 'state of art' in this area. The chapters are written by leading teams and researchers in this field of study, mainly from Europe, North America and Australasia. Considerable progress has been made in topics dealing with: modelling methods, feeding behaviour, digestion and metabolic processes in ruminants and monogastric animals. This progress is clearly illustrated by the emergence of a new paradigm in animal nutrition, which has moved from the aim to cover the requirements of the animal to explaining and predicting the responses of the animals to diets (e.g., productivity and efficiency, impact on quality of products, environmental aspects, health and well-being). In this book several chapters illustrate that through empirical models, meta-analysis is an efficient tool to synthesize information gathered over recent decades. In addition, compared with other books on modelling farm animal nutrition, two new aspects received particular attention: expanding knowledge of the individual animal to understanding the functioning and management of herds, and the consideration of the environmental impact of animal production. This book is a valuable source of information for researchers, nutritionists, advisors, and graduate students who want to have up-to-date and concise information on mathematical modelling applied to farm animals.

R In A Nutshell

Author : Joseph Adler
ISBN : 9783897216501
Genre : Computers
File Size : 77. 73 MB
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Wozu sollte man R lernen? Da gibt es viele Gründe: Weil man damit natürlich ganz andere Möglichkeiten hat als mit einer Tabellenkalkulation wie Excel, aber auch mehr Spielraum als mit gängiger Statistiksoftware wie SPSS und SAS. Anders als bei diesen Programmen hat man nämlich direkten Zugriff auf dieselbe, vollwertige Programmiersprache, mit der die fertigen Analyse- und Visualisierungsmethoden realisiert sind – so lassen sich nahtlos eigene Algorithmen integrieren und komplexe Arbeitsabläufe realisieren. Und nicht zuletzt, weil R offen gegenüber beliebigen Datenquellen ist, von der einfachen Textdatei über binäre Fremdformate bis hin zu den ganz großen relationalen Datenbanken. Zudem ist R Open Source und erobert momentan von der universitären Welt aus die professionelle Statistik. R kann viel. Und Sie können viel mit R machen – wenn Sie wissen, wie es geht. Willkommen in der R-Welt: Installieren Sie R und stöbern Sie in Ihrem gut bestückten Werkzeugkasten: Sie haben eine Konsole und eine grafische Benutzeroberfläche, unzählige vordefinierte Analyse- und Visualisierungsoperationen – und Pakete, Pakete, Pakete. Für quasi jeden statistischen Anwendungsbereich können Sie sich aus dem reichen Schatz der R-Community bedienen. Sprechen Sie R! Sie müssen Syntax und Grammatik von R nicht lernen – wie im Auslandsurlaub kommen Sie auch hier gut mit ein paar aufgeschnappten Brocken aus. Aber es lohnt sich: Wenn Sie wissen, was es mit R-Objekten auf sich hat, wie Sie eigene Funktionen schreiben und Ihre eigenen Pakete schnüren, sind Sie bei der Analyse Ihrer Daten noch flexibler und effektiver. Datenanalyse und Statistik in der Praxis: Anhand unzähliger Beispiele aus Medizin, Wirtschaft, Sport und Bioinformatik lernen Sie, wie Sie Daten aufbereiten, mithilfe der Grafikfunktionen des lattice-Pakets darstellen, statistische Tests durchführen und Modelle anpassen. Danach werden Ihnen Ihre Daten nichts mehr verheimlichen.

Einf Hrung In S Und S Plus

Author : Andreas Krause
ISBN : 9783642603921
Genre : Mathematics
File Size : 72. 56 MB
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Eine moderne Sprache für interaktive Datenanalyse in moderner, klarer Präsentation! Zum Verständnis sind nur geringe Vorkenntnisse in Statistik und Programmierung nötig. Der Leser wird Schritt für Schritt in die Anwendungen und Vorteile des Systems eingeführt. Zahlreiche Beispiele und eine umfangreiche Aufgabensammlung mit vollständig ausgearbeiteten Lösungen erleichtern das Lernen.

Introductory Statistics With R

Author : Peter Dalgaard
ISBN : 9780387790541
Genre : Mathematics
File Size : 44. 11 MB
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This book provides an elementary-level introduction to R, targeting both non-statistician scientists in various fields and students of statistics. The main mode of presentation is via code examples with liberal commenting of the code and the output, from the computational as well as the statistical viewpoint. Brief sections introduce the statistical methods before they are used. A supplementary R package can be downloaded and contains the data sets. All examples are directly runnable and all graphics in the text are generated from the examples. The statistical methodology covered includes statistical standard distributions, one- and two-sample tests with continuous data, regression analysis, one-and two-way analysis of variance, regression analysis, analysis of tabular data, and sample size calculations. In addition, the last four chapters contain introductions to multiple linear regression analysis, linear models in general, logistic regression, and survival analysis.

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