Linear Mixed Models In Practice
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Linear Mixed Models In Practice
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Author : Geert Verbeke
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Linear Mixed Models In Practice written by Geert Verbeke and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Medical categories.
The dissemination of the MIXED procedure in SAS has provided a whole class of statistical models for routine use. We believe that both the ideas be hind the techniques and their implementation in SAS are not at all straight forward and users from various applied backgrounds, including the phar maceutical industry, have experienced difficulties in using the procedure effectively. Courses and consultancy on PROC MIXED have been in great demand in recent years, illustrating the clear need for resource material to aid the user. This book is intended as a contribution to bridging this gap. We hope the book will be of value to a wide audience, including applied statisticians and many biomedical researchers, particularly in the pharma ceutical industry, medical and public health research organizations, con tract research organizations, and academic departments. This implies that our book is explanatory rather than research oriented and that it empha sizes practice rather than mathematical rigor. In this respect, clear guidance and advice on practical issues are the main focus of the text. Nevertheless, this does not imply that more advanced topics have been avoided. Sections containing material of a deeper level have been sign posted by means of an asterisk.
Linear Mixed Models In Practice
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Author : Geert Verbeke
language : en
Publisher:
Release Date : 1997-08-01
Linear Mixed Models In Practice written by Geert Verbeke and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997-08-01 with categories.
Robust Mixed Model Analysis
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Author : Jiming Jiang
language : en
Publisher: World Scientific
Release Date : 2019-04-05
Robust Mixed Model Analysis written by Jiming Jiang and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-05 with Mathematics categories.
Mixed-effects models have found broad applications in various fields. As a result, the interest in learning and using these models is rapidly growing. On the other hand, some of these models, such as the linear mixed models and generalized linear mixed models, are highly parametric, involving distributional assumptions that may not be satisfied in real-life problems. Therefore, it is important, from a practical standpoint, that the methods of inference about these models are robust to violation of model assumptions. Fortunately, there is a full scale of methods currently available that are robust in certain aspects. Learning about these methods is essential for the practice of mixed-effects models.This research monograph provides a comprehensive account of methods of mixed model analysis that are robust in various aspects, such as to violation of model assumptions, or to outliers. It is suitable as a reference book for a practitioner who uses the mixed-effects models, and a researcher who studies these models. It can also be treated as a graduate text for a course on mixed-effects models and their applications.
Linear And Generalized Linear Mixed Models And Their Applications
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Author : Jiming Jiang
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-05-30
Linear And Generalized Linear Mixed Models And Their Applications written by Jiming Jiang and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-05-30 with Mathematics categories.
Over the past decade there has been an explosion of developments in mixed e?ects models and their applications. This book concentrates on two major classes of mixed e?ects models, linear mixed models and generalized linear mixed models, with the intention of o?ering an up-to-date account of theory and methods in the analysis of these models as well as their applications in various ?elds. The ?rst two chapters are devoted to linear mixed models. We classify l- ear mixed models as Gaussian (linear) mixed models and non-Gaussian linear mixed models. There have been extensive studies in estimation in Gaussian mixed models as well as tests and con?dence intervals. On the other hand, the literature on non-Gaussian linear mixed models is much less extensive, partially because of the di?culties in inference about these models. However, non-Gaussian linear mixed models are important because, in practice, one is never certain that normality holds. This book o?ers a systematic approach to inference about non-Gaussian linear mixed models. In particular, it has included recently developed methods, such as partially observed information, iterative weighted least squares, and jackknife in the context of mixed models. Other new methods introduced in this book include goodness-of-?t tests, p- diction intervals, and mixed model selection. These are, of course, in addition to traditional topics such as maximum likelihood and restricted maximum likelihood in Gaussian mixed models.
Models And Estimation Of Genetic Effects
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Author : José M Álvarez-Castro
language : en
Publisher: Frontiers Media SA
Release Date : 2015-04-17
Models And Estimation Of Genetic Effects written by José M Álvarez-Castro and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-04-17 with Ecology categories.
Ronald Fisher needed to develop elaborate models of genetic effects in order to set the foundations of Quantitative Genetics in his 1918 paper “The correlation between relatives on the supposition of Mendelian inheritance”. Since then, many significant implementations have been made to model genetic effects. However, at the verge of one century after Fisher’s kick-off, models of genetic effects keep on being discussed and implemented. Indeed, the relatively recent advent of QTL analyses challenged the state of the art of this field by providing researchers the opportunity to obtain and analyze estimates of genetic effects from real data. In this context, the development of this field was not exempt of some polemics, like the debate about the convenience of the functional and the statistical epistasis approaches. This research topic is meant to provide recent developments in models and estimation of genetic effects and to enrich the discussion about how and why models of genetic effects must be further developed and applied. The articles in this Research Topic shall thus extend, refine and/or provide a refresh look at Fisher’s original models of genetic effects and their application to genetic effects estimation and to improve our understanding of evolutionary processes and breeding programs.
Predictive Modeling Applications In Actuarial Science
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Author : Edward W. Frees
language : en
Publisher: Cambridge University Press
Release Date : 2014-07-28
Predictive Modeling Applications In Actuarial Science written by Edward W. Frees and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-07-28 with Business & Economics categories.
This book is for actuaries and financial analysts developing their expertise in statistics and who wish to become familiar with concrete examples of predictive modeling.
Linear Mixed Models
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Author : Brady T. West
language : en
Publisher: CRC Press
Release Date : 2014-07-17
Linear Mixed Models written by Brady T. West and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-07-17 with Mathematics categories.
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
Dynamical Biostatistical Models
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Author : Daniel Commenges
language : en
Publisher: CRC Press
Release Date : 2015-10-02
Dynamical Biostatistical Models written by Daniel Commenges and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-10-02 with Mathematics categories.
Dynamical Biostatistical Models presents statistical models and methods for the analysis of longitudinal data. The book focuses on models for analyzing repeated measures of quantitative and qualitative variables and events history, including survival and multistate models. Most of the advanced methods, such as multistate and joint models, can be ap
Improving Sustainable Viticulture And Winemaking Practices
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Author : J. Miguel Costa
language : en
Publisher: Academic Press
Release Date : 2022-03-19
Improving Sustainable Viticulture And Winemaking Practices written by J. Miguel Costa and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-19 with Technology & Engineering categories.
Improving Sustainable Practices in Viticulture and Enology provides an up-to-date view on the major issues concerning the sustainability of the wine supply chain. The book describes problems and solutions on the use of inputs (e.g., water, energy) and emphasizes the roles and limitations of implementing circularity in the sector. It identifies some of the most relevant metrics while pinpointing the most critical issues concerning the environmental impacts of wine's supply chain (vineyards, wineries, trading). This is a novel reference to help the industry excel in production while improving current environmental practices. Professionals in industry, academics, environmentalists and anyone interested in gaining knowledge in sustainable solutions and practices in viticulture and wine production will find this resource indispensable. - Suggests and discusses solutions to overcome challenges imposed by adverse climate conditions - Presents innovative technologies that have an impact on the efficiency of resources and recycling - Includes technological tools for more precise monitoring and management in the wine supply chain
Generalized Linear Mixed Models
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Author : Walter W. Stroup
language : en
Publisher: CRC Press
Release Date : 2024-05-21
Generalized Linear Mixed Models written by Walter W. Stroup and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-21 with Mathematics categories.
Generalized Linear Mixed Models: Modern Concepts, Methods, and Applications (2nd edition) presents an updated introduction to linear modeling using the generalized linear mixed model (GLMM) as the overarching conceptual framework. For students new to statistical modeling, this book helps them see the big picture – linear modeling as broadly understood and its intimate connection with statistical design and mathematical statistics. For readers experienced in statistical practice, but new to GLMMs, the book provides a comprehensive introduction to GLMM methodology and its underlying theory. Unlike textbooks that focus on classical linear models or generalized linear models or mixed models, this book covers all of the above as members of a unified GLMM family of linear models. In addition to essential theory and methodology, this book features a rich collection of examples using SAS® software to illustrate GLMM practice. This second edition is updated to reflect lessons learned and experience gained regarding best practices and modeling choices faced by GLMM practitioners. New to this edition are two chapters focusing on Bayesian methods for GLMMs. Key Features: Most statistical modeling books cover classical linear models or advanced generalized and mixed models; this book covers all members of the GLMM family – classical and advanced models Incorporates lessons learned from experience and on-going research to provide up-to-date examples of best practices Illustrates connections between statistical design and modeling: guidelines for translating study design into appropriate model and in-depth illustrations of how to implement these guidelines; use of GLMM methods to improve planning and design Discusses the difference between marginal and conditional models, differences in the inference space they are intended to address and when each type of model is appropriate In addition to likelihood-based frequentist estimation and inference, provides a brief introduction to Bayesian methods for GLMMs