Introduction To Mixed Modelling

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Introduction to Mixed Modelling

Author : N. W. Galwey
Publisher : John Wiley & Sons
ISBN 13 : 047003596X
Total Pages : 379 pages
Book Rating : 4.4/5 (7 download)

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Book Synopsis Introduction to Mixed Modelling by : N. W. Galwey

Download or read book Introduction to Mixed Modelling written by N. W. Galwey and published by John Wiley & Sons. This book was released on 2007-04-04 with total page 379 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mixed modelling is one of the most promising and exciting areas ofstatistical analysis, enabling more powerful interpretation of datathrough the recognition of random effects. However, many perceivemixed modelling as an intimidating and specialized technique. Thisbook introduces mixed modelling analysis in a simple andstraightforward way, allowing the reader to apply the techniqueconfidently in a wide range of situations. Introduction to Mixed Modelling shows that mixedmodelling is a natural extension of the more familiar statisticalmethods of regression analysis and analysis of variance. In doingso, it provides the ideal introduction to this importantstatistical technique for those engaged in the statistical analysisof data. This essential book: Demonstrates the power of mixed modelling in a wide range ofdisciplines, including industrial research, social sciences,genetics, clinical research, ecology and agriculturalresearch. Illustrates how the capabilities of regression analysis can becombined with those of ANOVA by the specification of a mixedmodel. Introduces the criterion of Restricted Maximum Likelihood(REML) for the fitting of a mixed model to data. Presents the application of mixed model analysis to a widerange of situations and explains how to obtain and interpret BestLinear Unbiased Predictors (BLUPs). Features a supplementary website containing solutions toexercises, further examples, and links to the computer softwaresystems GenStat and R. This book provides a comprehensive introduction to mixedmodelling, ideal for final year undergraduate students,postgraduate students and professional researchers alike. Readerswill come from a wide range of scientific disciplines includingstatistics, biology, bioinformatics, medicine, agriculture,engineering, economics, and social sciences.

SAS for Mixed Models

Author : Walter W. Stroup
Publisher : SAS Institute
ISBN 13 : 163526152X
Total Pages : 608 pages
Book Rating : 4.6/5 (352 download)

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Book Synopsis SAS for Mixed Models by : Walter W. Stroup

Download or read book SAS for Mixed Models written by Walter W. Stroup and published by SAS Institute. This book was released on 2018-12-12 with total page 608 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover the power of mixed models with SAS. Mixed models—now the mainstream vehicle for analyzing most research data—are part of the core curriculum in most master’s degree programs in statistics and data science. In a single volume, this book updates both SAS® for Linear Models, Fourth Edition, and SAS® for Mixed Models, Second Edition, covering the latest capabilities for a variety of applications featuring the SAS GLIMMIX and MIXED procedures. Written for instructors of statistics, graduate students, scientists, statisticians in business or government, and other decision makers, SAS® for Mixed Models is the perfect entry for those with a background in two-way analysis of variance, regression, and intermediate-level use of SAS. This book expands coverage of mixed models for non-normal data and mixed-model-based precision and power analysis, including the following topics: Random-effect-only and random-coefficients models Multilevel, split-plot, multilocation, and repeated measures models Hierarchical models with nested random effects Analysis of covariance models Generalized linear mixed models This book is part of the SAS Press program.

Mixed-Effects Models in S and S-PLUS

Author : José C. Pinheiro
Publisher : Springer Science & Business Media
ISBN 13 : 1441903178
Total Pages : 538 pages
Book Rating : 4.4/5 (419 download)

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Book Synopsis Mixed-Effects Models in S and S-PLUS by : José C. Pinheiro

Download or read book Mixed-Effects Models in S and S-PLUS written by José C. Pinheiro and published by Springer Science & Business Media. This book was released on 2009-04-15 with total page 538 pages. Available in PDF, EPUB and Kindle. Book excerpt: R, linear models, random, fixed, data, analysis, fit.

New Methods in Cognitive Psychology

Author : Daniel Spieler
Publisher : Routledge
ISBN 13 : 1000617467
Total Pages : 292 pages
Book Rating : 4.0/5 (6 download)

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Book Synopsis New Methods in Cognitive Psychology by : Daniel Spieler

Download or read book New Methods in Cognitive Psychology written by Daniel Spieler and published by Routledge. This book was released on 2019-10-28 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an overview of cutting-edge methods currently being used in cognitive psychology, which are likely to appear with increasing frequency in coming years. Once built around univariate parametric statistics, cognitive psychology courses now seem deficient without some contact with methods for signal processing, spatial statistics, and machine learning. There are also important changes in analyses of behavioral data (e.g., hierarchical modeling and Bayesian inference) and there is the obvious change wrought by the advancement of functional imaging. This book begins by discussing the evidence of this rapid change, for example the movement between using traditional analyses of variance to multi-level mixed models, in psycholinguistics. It then goes on to discuss the methods for analyses of physiological measurements, and how these methods provide insights into cognitive processing. New Methods in Cognitive Psychology provides senior undergraduates, graduates and researchers with cutting-edge overviews of new and emerging topics, and the very latest in theory and research for the more established topics.

Mixed Models

Author : Eugene Demidenko
Publisher : John Wiley & Sons
ISBN 13 : 0471726133
Total Pages : 732 pages
Book Rating : 4.4/5 (717 download)

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Book Synopsis Mixed Models by : Eugene Demidenko

Download or read book Mixed Models written by Eugene Demidenko and published by John Wiley & Sons. This book was released on 2005-01-28 with total page 732 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 Mixed model as a compromise between the frequentist and Bayesian approaches Mixed model for the penalized log-likelihood Healthy Akaike Information Criterion (HAIC) How to cope with parameter multidimensionality How to solve ill-posed problems including image reconstruction problems Modeling of ensemble shapes and images Statistics of image processing Major results and points of discussion at the end of each chapter along with "Summary Points" sections make this reference not only comprehensive but also highly accessible for professionals and students alike in a broad range of fields such as cancer research, computer science, engineering, and industry.

Linear mixed models. An introduction with applications in veterinary research

Author : Duchateau, L.
Publisher : ILRI (aka ILCA and ILRAD)
ISBN 13 : 9789291460380
Total Pages : 172 pages
Book Rating : 4.4/5 (63 download)

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Book Synopsis Linear mixed models. An introduction with applications in veterinary research by : Duchateau, L.

Download or read book Linear mixed models. An introduction with applications in veterinary research written by Duchateau, L. and published by ILRI (aka ILCA and ILRAD). This book was released on 1998-01-01 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Mixed Effects Models for Complex Data

Author : Lang Wu
Publisher : CRC Press
ISBN 13 : 9781420074086
Total Pages : 431 pages
Book Rating : 4.0/5 (74 download)

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Book Synopsis Mixed Effects Models for Complex Data by : Lang Wu

Download or read book Mixed Effects Models for Complex Data written by Lang Wu and published by CRC Press. This book was released on 2009-11-11 with total page 431 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although standard mixed effects models are useful in a range of studies, other approaches must often be used in correlation with them when studying complex or incomplete data. Mixed Effects Models for Complex Data discusses commonly used mixed effects models and presents appropriate approaches to address dropouts, missing data, measurement errors, censoring, and outliers. For each class of mixed effects model, the author reviews the corresponding class of regression model for cross-sectional data. An overview of general models and methods, along with motivating examples After presenting real data examples and outlining general approaches to the analysis of longitudinal/clustered data and incomplete data, the book introduces linear mixed effects (LME) models, generalized linear mixed models (GLMMs), nonlinear mixed effects (NLME) models, and semiparametric and nonparametric mixed effects models. It also includes general approaches for the analysis of complex data with missing values, measurement errors, censoring, and outliers. Self-contained coverage of specific topics Subsequent chapters delve more deeply into missing data problems, covariate measurement errors, and censored responses in mixed effects models. Focusing on incomplete data, the book also covers survival and frailty models, joint models of survival and longitudinal data, robust methods for mixed effects models, marginal generalized estimating equation (GEE) models for longitudinal or clustered data, and Bayesian methods for mixed effects models. Background material In the appendix, the author provides background information, such as likelihood theory, the Gibbs sampler, rejection and importance sampling methods, numerical integration methods, optimization methods, bootstrap, and matrix algebra. Failure to properly address missing data, measurement errors, and other issues in statistical analyses can lead to severely biased or misleading results. This book explores the biases that arise when naïve methods are used and shows which approaches should be used to achieve accurate results in longitudinal data analysis.

Linear Mixed Models

Author : Brady T. West
Publisher : CRC Press
ISBN 13 : 1420010433
Total Pages : 376 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Linear Mixed Models by : Brady T. West

Download or read book Linear Mixed Models written by Brady T. West and published by CRC Press. This book was released on 2006-11-22 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: Simplifying the often confusing array of software programs for fitting linear mixed models (LMMs), Linear Mixed Models: A Practical Guide Using Statistical Software provides a basic introduction to primary concepts, notation, software implementation, model interpretation, and visualization of clustered and longitudinal data. This easy-to-nav

Generalized Linear Mixed Models

Author : Walter W. Stroup
Publisher : CRC Press
ISBN 13 : 1439815135
Total Pages : 547 pages
Book Rating : 4.4/5 (398 download)

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Book Synopsis Generalized Linear Mixed Models by : Walter W. Stroup

Download or read book Generalized Linear Mixed Models written by Walter W. Stroup and published by CRC Press. This book was released on 2016-04-19 with total page 547 pages. Available in PDF, EPUB and Kindle. Book excerpt: With numerous examples using SAS PROC GLIMMIX, this text presents an introduction to linear modeling using the generalized linear mixed model as an overarching conceptual framework. For readers new to linear models, the book helps them see the big picture. It shows how linear models fit with the rest of the core statistics curriculum and points out the major issues that statistical modelers must consider.

Mixed Models

Author : Eugene Demidenko
Publisher : John Wiley & Sons
ISBN 13 : 1118091574
Total Pages : 768 pages
Book Rating : 4.1/5 (18 download)

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Book Synopsis Mixed Models by : Eugene Demidenko

Download or read book Mixed Models written by Eugene Demidenko and published by John Wiley & Sons. This book was released on 2013-08-05 with total page 768 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 models’ statistical properties and numerical algorithms, as well as nontraditional applications, such as regrowth curves, shapes, and images. The book features the latest topics in statistics including modeling of complex clustered or longitudinal data, modeling data with multiple sources of variation, modeling biological variety and heterogeneity, Healthy Akaike Information Criterion (HAIC), parameter multidimensionality, and statistics of image processing. Mixed Models: Theory and Applications with R, Second Edition features unique applications of mixed model methodology, as well as: Comprehensive theoretical discussions illustrated by examples and figures Over 300 exercises, end-of-section problems, updated data sets, and R subroutines Problems and extended projects requiring simulations in R intended to reinforce material Summaries of major results and general points of discussion at the end of each chapter Open problems in mixed modeling methodology, which can be used as the basis for research or PhD dissertations Ideal for graduate-level courses in mixed statistical modeling, the book is also an excellent reference for professionals in a range of fields, including cancer research, computer science, and engineering.

Linear Mixed-Effects Models Using R

Author : Andrzej Gałecki
Publisher : Springer Science & Business Media
ISBN 13 : 1461439000
Total Pages : 558 pages
Book Rating : 4.4/5 (614 download)

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Book Synopsis Linear Mixed-Effects Models Using R by : Andrzej Gałecki

Download or read book Linear Mixed-Effects Models Using R written by Andrzej Gałecki and published by Springer Science & Business Media. This book was released on 2013-02-05 with total page 558 pages. Available in PDF, EPUB and Kindle. Book excerpt: Linear mixed-effects models (LMMs) are an important class of statistical models that can be used to analyze correlated data. Such data are encountered in a variety of fields including biostatistics, public health, psychometrics, educational measurement, and sociology. This book aims to support a wide range of uses for the models by applied researchers in those and other fields by providing state-of-the-art descriptions of the implementation of LMMs in R. To help readers to get familiar with the features of the models and the details of carrying them out in R, the book includes a review of the most important theoretical concepts of the models. The presentation connects theory, software and applications. It is built up incrementally, starting with a summary of the concepts underlying simpler classes of linear models like the classical regression model, and carrying them forward to LMMs. A similar step-by-step approach is used to describe the R tools for LMMs. All the classes of linear models presented in the book are illustrated using real-life data. The book also introduces several novel R tools for LMMs, including new class of variance-covariance structure for random-effects, methods for influence diagnostics and for power calculations. They are included into an R package that should assist the readers in applying these and other methods presented in this text.

Mixed Effects Models and Extensions in Ecology with R

Author : Alain Zuur
Publisher : Springer Science & Business Media
ISBN 13 : 0387874585
Total Pages : 579 pages
Book Rating : 4.3/5 (878 download)

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Book Synopsis Mixed Effects Models and Extensions in Ecology with R by : Alain Zuur

Download or read book Mixed Effects Models and Extensions in Ecology with R written by Alain Zuur and published by Springer Science & Business Media. This book was released on 2009-03-05 with total page 579 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses advanced statistical methods that can be used to analyse ecological data. Most environmental collected data are measured repeatedly over time, or space and this requires the use of GLMM or GAMM methods. The book starts by revising regression, additive modelling, GAM and GLM, and then discusses dealing with spatial or temporal dependencies and nested data.

Linear Mixed Models

Author : Brady T. West
Publisher : CRC Press
ISBN 13 : 1466560991
Total Pages : 442 pages
Book Rating : 4.4/5 (665 download)

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Book Synopsis Linear Mixed Models by : Brady T. West

Download or read book Linear Mixed Models written by Brady T. West and published by CRC Press. This book was released on 2014-07-17 with total page 442 pages. Available in PDF, EPUB and Kindle. Book excerpt: Highly recommended by JASA, Technometrics, and other journals, the first edition of this bestseller showed how to easily perform complex linear mixed model (LMM) analyses via a variety of software programs. Linear Mixed Models: A Practical Guide Using Statistical Software, Second Edition continues to lead readers step by step through the process of fitting LMMs. This second edition covers additional topics on the application of LMMs that are valuable for data analysts in all fields. It also updates the case studies using the latest versions of the software procedures and provides up-to-date information on the options and features of the software procedures available for fitting LMMs in SAS, SPSS, Stata, R/S-plus, and HLM. New to the Second Edition A new chapter on models with crossed random effects that uses a case study to illustrate software procedures capable of fitting these models Power analysis methods for longitudinal and clustered study designs, including software options for power analyses and suggested approaches to writing simulations Use of the lmer() function in the lme4 R package New sections on fitting LMMs to complex sample survey data and Bayesian approaches to making inferences based on LMMs Updated graphical procedures in the software packages Substantially revised index to enable more efficient reading and easier location of material on selected topics or software options More practical recommendations on using the software for analysis A new R package (WWGbook) that contains all of the data sets used in the examples Ideal for anyone who uses software for statistical modeling, this book eliminates the need to read multiple software-specific texts by covering the most popular software programs for fitting LMMs in one handy guide. The authors illustrate the models and methods through real-world examples that enable comparisons of model-fitting options and results across the software procedures.

Applied Mixed Models in Medicine

Author : Helen Brown
Publisher : John Wiley & Sons
ISBN 13 : 1118778243
Total Pages : 536 pages
Book Rating : 4.1/5 (187 download)

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Book Synopsis Applied Mixed Models in Medicine by : Helen Brown

Download or read book Applied Mixed Models in Medicine written by Helen Brown and published by John Wiley & Sons. This book was released on 2014-12-12 with total page 536 pages. Available in PDF, EPUB and Kindle. Book excerpt: A fully updated edition of this key text on mixed models, focusing on applications in medical research The application of mixed models is an increasingly popular way of analysing medical data, particularly in the pharmaceutical industry. A mixed model allows the incorporation of both fixed and random variables within a statistical analysis, enabling efficient inferences and more information to be gained from the data. There have been many recent advances in mixed modelling, particularly regarding the software and applications. This third edition of Brown and Prescott’s groundbreaking text provides an update on the latest developments, and includes guidance on the use of current SAS techniques across a wide range of applications. Presents an overview of the theory and applications of mixed models in medical research, including the latest developments and new sections on incomplete block designs and the analysis of bilateral data. Easily accessible to practitioners in any area where mixed models are used, including medical statisticians and economists. Includes numerous examples using real data from medical and health research, and epidemiology, illustrated with SAS code and output. Features the new version of SAS, including new graphics for model diagnostics and the procedure PROC MCMC. Supported by a website featuring computer code, data sets, and further material. This third edition will appeal to applied statisticians working in medical research and the pharmaceutical industry, as well as teachers and students of statistics courses in mixed models. The book will also be of great value to a broad range of scientists, particularly those working in the medical and pharmaceutical areas.

Applied Mixed Model Analysis

Author : Jos W. R. Twisk
Publisher : Cambridge University Press
ISBN 13 : 1108480578
Total Pages : 249 pages
Book Rating : 4.1/5 (84 download)

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Book Synopsis Applied Mixed Model Analysis by : Jos W. R. Twisk

Download or read book Applied Mixed Model Analysis written by Jos W. R. Twisk and published by Cambridge University Press. This book was released on 2019-04-18 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: Emphasizing interpretation of results, this hands-on guide explains why, when, and how to use mixed models with your data.

SAS for Mixed Models

Author : Ramon C. Littell
Publisher : SAS Press
ISBN 13 : 9781590475003
Total Pages : 814 pages
Book Rating : 4.4/5 (75 download)

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Book Synopsis SAS for Mixed Models by : Ramon C. Littell

Download or read book SAS for Mixed Models written by Ramon C. Littell and published by SAS Press. This book was released on 2006 with total page 814 pages. Available in PDF, EPUB and Kindle. Book excerpt: This indispensable guide to mixed models using SAS is completely revised and updated for SAS 9. Discover the latest capabilities available for a variety of applications featuring the MIXED, GLIMMIX, and NLMIXED procedures.

An R Companion to Applied Regression

Author : John Fox
Publisher : SAGE Publications
ISBN 13 : 1544336454
Total Pages : 505 pages
Book Rating : 4.5/5 (443 download)

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Book Synopsis An R Companion to Applied Regression by : John Fox

Download or read book An R Companion to Applied Regression written by John Fox and published by SAGE Publications. This book was released on 2018-09-27 with total page 505 pages. Available in PDF, EPUB and Kindle. Book excerpt: An R Companion to Applied Regression is a broad introduction to the R statistical computing environment in the context of applied regression analysis. John Fox and Sanford Weisberg provide a step-by-step guide to using the free statistical software R, an emphasis on integrating statistical computing in R with the practice of data analysis, coverage of generalized linear models, and substantial web-based support materials. The Third Edition has been reorganized and includes a new chapter on mixed-effects models, new and updated data sets, and a de-emphasis on statistical programming, while retaining a general introduction to basic R programming. The authors have substantially updated both the car and effects packages for R for this edition, introducing additional capabilities and making the software more consistent and easier to use. They also advocate an everyday data-analysis workflow that encourages reproducible research. To this end, they provide coverage of RStudio, an interactive development environment for R that allows readers to organize and document their work in a simple and intuitive fashion, and then easily share their results with others. Also included is coverage of R Markdown, showing how to create documents that mix R commands with explanatory text. "An R Companion to Applied Regression continues to provide the most comprehensive and user-friendly guide to estimating, interpreting, and presenting results from regression models in R." –Christopher Hare, University of California, Davis