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 : 39. 31 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 : 81. 33 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 : 81. 27 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 : 83. 71 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.

Modelling Nutrient Digestion And Utilisation In Farm Animals

Author : D. Sauvant
ISBN : 9789086867127
Genre : Science
File Size : 76. 62 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.

Introductory Statistics With R

Author : Peter Dalgaard
ISBN : 9780387790541
Genre : Mathematics
File Size : 77. 44 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.

Computational Methods For Mixed Up Effects Models

Author : Saikat DebRoy
ISBN : WISC:89083392597
Genre :
File Size : 72. 59 MB
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Applied Longitudinal Data Analysis

Author : Judith D. Singer
ISBN : 9780199882403
Genre : Psychology
File Size : 49. 69 MB
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Change is constant in everyday life. Infants crawl and then walk, children learn to read and write, teenagers mature in myriad ways, the elderly become frail and forgetful. Beyond these natural processes and events, external forces and interventions instigate and disrupt change: test scores may rise after a coaching course, drug abusers may remain abstinent after residential treatment. By charting changes over time and investigating whether and when events occur, researchers reveal the temporal rhythms of our lives. Applied Longitudinal Data Analysis is a much-needed professional book for empirical researchers and graduate students in the behavioral, social, and biomedical sciences. It offers the first accessible in-depth presentation of two of today's most popular statistical methods: multilevel models for individual change and hazard/survival models for event occurrence (in both discrete- and continuous-time). Using clear, concise prose and real data sets from published studies, the authors take you step by step through complete analyses, from simple exploratory displays that reveal underlying patterns through sophisticated specifications of complex statistical models. Applied Longitudinal Data Analysis offers readers a private consultation session with internationally recognized experts and represents a unique contribution to the literature on quantitative empirical methods. Visit http://www.ats.ucla.edu/stat/examples/alda.htm for: · Downloadable data sets · Library of computer programs in SAS, SPSS, Stata, HLM, MLwiN, and more · Additional material for data analysis

Modern Applied Statistics With S Plus

Author : William N. Venables
ISBN : 9781475727197
Genre : Mathematics
File Size : 64. 96 MB
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A guide to using the power of S-PLUS to perform statistical analyses, providing both an introduction to the program and a course in modern statistical methods. Readers are assumed to have a basic grounding in statistics, thus the book is intended for would-be users, as well as students and researchers using statistics. Throughout, the emphasis is on presenting practical problems and full analyses of real data sets, with many of the methods discussed being modern approaches to topics such as linear and non-linear regression models, robust and smooth regression methods, survival analysis, multivariate analysis, tree-based methods, time series, spatial statistics, and classification. This second edition is intended for users of S-PLUS 3.3, or later, and covers both Windows and UNIX. It treats the recent developments in graphics and new statistical functionality, including bootstraping, mixed effects linear and non-linear models, factor analysis, and regression with autocorrelated errors. The authors have written several software libraries which enhance S-PLUS, and these, plus all the datasets used, are available on the Internet.

Canadian Journal Of Forest Research

Author :
ISBN : MINN:31951P011860426
Genre : Forests and forestry
File Size : 51. 75 MB
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