Linear and Nonlinear Mixed-effects Models for Repeated Measures Data PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Linear and Nonlinear Mixed-effects Models for Repeated Measures Data PDF full book. Access full book title Linear and Nonlinear Mixed-effects Models for Repeated Measures Data by Mary Judith Lindstrom. Download full books in PDF and EPUB format.
Author: Mary Judith Lindstrom
Publisher:
ISBN:
Category : Linear models (Statistics)
Languages : en
Pages : 332
Get Book Here
Book Description
Author: Mary Judith Lindstrom
Publisher:
ISBN:
Category : Linear models (Statistics)
Languages : en
Pages : 332
Get Book Here
Book Description
Author: Edward Vonesh
Publisher: CRC Press
ISBN: 9780824782481
Category : Mathematics
Languages : en
Pages : 590
Get Book Here
Book Description
Integrates the latest theory, methodology and applications related to the design and analysis of repeated measurement. The text covers a broad range of topics, including the analysis of repeated measures design, general crossover designs, and linear and nonlinear regression models. It also contains a 3.5 IBM compatible disk, with software to implement immediately the techniques.
Author: Marie Davidian
Publisher: Routledge
ISBN: 1351428152
Category : Mathematics
Languages : en
Pages : 360
Get Book Here
Book Description
Nonlinear measurement data arise in a wide variety of biological and biomedical applications, such as longitudinal clinical trials, studies of drug kinetics and growth, and the analysis of assay and laboratory data. Nonlinear Models for Repeated Measurement Data provides the first unified development of methods and models for data of this type, with a detailed treatment of inference for the nonlinear mixed effects and its extensions. A particular strength of the book is the inclusion of several detailed case studies from the areas of population pharmacokinetics and pharmacodynamics, immunoassay and bioassay development and the analysis of growth curves.
Author: José C. Pinheiro
Publisher: Springer Science & Business Media
ISBN: 1441903178
Category : Computers
Languages : en
Pages : 538
Get Book Here
Book Description
R, linear models, random, fixed, data, analysis, fit.
Author: Lang Wu
Publisher: CRC Press
ISBN: 9781420074086
Category : Mathematics
Languages : en
Pages : 431
Get Book Here
Book Description
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.
Author: Marie Davidian
Publisher: Routledge
ISBN: 1351428144
Category : Mathematics
Languages : en
Pages : 380
Get Book Here
Book Description
Nonlinear measurement data arise in a wide variety of biological and biomedical applications, such as longitudinal clinical trials, studies of drug kinetics and growth, and the analysis of assay and laboratory data. Nonlinear Models for Repeated Measurement Data provides the first unified development of methods and models for data of this type, with a detailed treatment of inference for the nonlinear mixed effects and its extensions. A particular strength of the book is the inclusion of several detailed case studies from the areas of population pharmacokinetics and pharmacodynamics, immunoassay and bioassay development and the analysis of growth curves.
Author: Mary Judith Lindstrom
Publisher:
ISBN:
Category :
Languages : en
Pages : 21
Get Book Here
Book Description
Author: Edward Vonesh
Publisher: CRC Press
ISBN: 9780367579555
Category :
Languages : en
Pages : 560
Get Book Here
Book Description
Integrates the latest theory, methodology and applications related to the design and analysis of repeated measurement. The text covers a broad range of topics, including the analysis of repeated measures design, general crossover designs, and linear and nonlinear regression models. It also contains a 3.5 IBM compatible disk, with software to implement immediately the techniques.
Author: Shelly Anne Blozis
Publisher:
ISBN:
Category :
Languages : en
Pages : 206
Get Book Here
Book Description
Author: Brady T. West
Publisher: CRC Press
ISBN: 1420010433
Category : Mathematics
Languages : en
Pages : 376
Get Book Here
Book Description
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
