Linear Mixed Models For Longitudinal Data

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Linear Mixed Models For Longitudinal Data

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Author : Geert Verbeke
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-04-28

Linear Mixed Models For Longitudinal Data 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 2009-04-28 with Mathematics categories.

This book provides a comprehensive treatment of linear mixed models for continuous longitudinal data. Next to model formulation, this edition puts major emphasis on exploratory data analysis for all aspects of the model, such as the marginal model, subject-specific profiles, and residual covariance structure. Further, model diagnostics and missing data receive extensive treatment. Sensitivity analysis for incomplete data is given a prominent place. Most analyses were done with the MIXED procedure of the SAS software package, but the data analyses are presented in a software-independent fashion.

Linear Mixed Models

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Author : Brady T. West
language : en
Publisher: CRC Press
Release Date : 2006-11-22

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 2006-11-22 with Mathematics categories.

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

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

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 For Longitudinal Data

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Author : Geert Verbeke
language : en
Publisher:
Release Date : 2014-01-15

Linear Mixed Models For Longitudinal Data 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 2014-01-15 with categories.

Non Standard Problems In Inference For Additive And Linear Mixed Models

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Author : Sonja Greven
language : en
Publisher: Cuvillier Verlag
Release Date : 2008

Non Standard Problems In Inference For Additive And Linear Mixed Models written by Sonja Greven and has been published by Cuvillier Verlag this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Inference categories.

Models For Discrete Longitudinal Data

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Author : Geert Molenberghs
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-01-28

Models For Discrete Longitudinal Data written by Geert Molenberghs 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 2006-01-28 with Mathematics categories.

The linear mixed model has become the main parametric tool for the analysis of continuous longitudinal data, as the authors discussed in their 2000 book. Without putting too much emphasis on software, the book shows how the different approaches can be implemented within the SAS software package. The authors received the American Statistical Association's Excellence in Continuing Education Award based on short courses on longitudinal and incomplete data at the Joint Statistical Meetings of 2002 and 2004.

Longitudinal Data Analysis

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Author : Ikuko Funatogawa
language : en
Publisher: Springer
Release Date : 2019-02-04

Longitudinal Data Analysis written by Ikuko Funatogawa and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-02-04 with Mathematics categories.

This book provides a new analytical approach for dynamic data repeatedly measured from multiple subjects over time. Random effects account for differences across subjects. Auto-regression in response itself is often used in time series analysis. In longitudinal data analysis, a static mixed effects model is changed into a dynamic one by the introduction of the auto-regression term. Response levels in this model gradually move toward an asymptote or equilibrium which depends on covariates and random effects. The book provides relationships of the autoregressive linear mixed effects models with linear mixed effects models, marginal models, transition models, nonlinear mixed effects models, growth curves, differential equations, and state space representation. State space representation with a modified Kalman filter provides log likelihoods for maximum likelihood estimation, and this representation is suitable for unequally spaced longitudinal data. The extension to multivariate longitudinal data analysis is also provided. Topics in medical fields, such as response-dependent dose modifications, response-dependent dropouts, and randomized controlled trials are discussed. The text is written in plain terms understandable for researchers in other disciplines such as econometrics, sociology, and ecology for the progress of interdisciplinary research.

Mixed Models

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Author : Eugene Demidenko
language : en
Publisher: John Wiley & Sons
Release Date : 2005-01-28

Mixed Models written by Eugene Demidenko and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-01-28 with Mathematics categories.

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.

Residual Analysis Of Linear Mixed Models For Longitudinal Data

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Author : Zhongxing Zhang
language : en
Publisher:
Release Date : 2016

Residual Analysis Of Linear Mixed Models For Longitudinal Data written by Zhongxing Zhang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with categories.