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Author : Haiyue Song
Publisher :
ISBN 13 :
Total Pages : 148 pages
Book Rating : 4.E/5 ( download)
Download or read book The Choice of Monte Carlo Algorithm in the Estimation of the Generalized Linear Mixed Model written by Haiyue Song and published by . This book was released on 2000 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Charles E. McCulloch
Publisher : IMS
ISBN 13 : 9780940600546
Total Pages : 100 pages
Book Rating : 4.6/5 (5 download)
Download or read book Generalized Linear Mixed Models written by Charles E. McCulloch and published by IMS. This book was released on 2003 with total page 100 pages. Available in PDF, EPUB and Kindle. Book excerpt: Wiley Series in Probability and Statistics A modern perspective on mixed models The availability of powerful computing methods in recent decades has thrust linear and nonlinear mixed models into the mainstream of statistical application. This volume offers a modern perspective on generalized, linear, and mixed models, presenting a unified and accessible treatment of the newest statistical methods for analyzing correlated, nonnormally distributed data. As a follow-up to Searle's classic, Linear Models, and Variance Components by Searle, Casella, and McCulloch, this new work progresses from the basic one-way classification to generalized linear mixed models. A variety of statistical methods are explained and illustrated, with an emphasis on maximum likelihood and restricted maximum likelihood. An invaluable resource for applied statisticians and industrial practitioners, as well as students interested in the latest results, Generalized, Linear, and Mixed Models features: * A review of the basics of linear models and linear mixed models * Descriptions of models for nonnormal data, including generalized linear and nonlinear models * Analysis and illustration of techniques for a variety of real data sets * Information on the accommodation of longitudinal data using these models * Coverage of the prediction of realized values of random effects * A discussion of the impact of computing issues on mixed models
Download or read book A Monte Carlo EM Algorithm for Generalized Linear Mixed Models with Flexible Random Effects Distribution written by and published by . This book was released on 2001 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: A popular way to model correlated binary, count, or other data arising inclinical trials and epidemiological studies of cancer and other diseases is byusing generalized linear mixed models (GLMMs), which acknowledge correlationthrough incorporation of random effects. A standard model assumption is thatthe random effects follow a parametric family such as the normal distribution. However, this may be unrealistic or too restrictive to represent the data, raising concern over the validity of inferences both on fixed and random effects if it is violated. Here we use the seminonparametric (SNP) approach (Davidian and Gallant 1992,1993) to model the random effects, which relaxes the normality assumption andjust requires that the distribution of random effects belong to a class of`"smooth'' densities given by Gallant and Nychka (1987). This representation allows the density of random effects to be very flexible, including densitiesthat are skewed, multi--modal, fat-- or thin--tailed relative to the normal, andthe normal as a special case. We also provide a reparameterization of this representation to avoid numerical instability in estimating the polynomialcoefficients. Because an efficient algorithm to sample from a SNP density is available, wepropose a Monte Carlo expectation maximization (MCEM) algorithm using arejection sampling scheme (Booth and Hobert, 1999) to estimate the fixedparameters of the linear predictor, variance components and the SNP density. Astrategy of choosing the degree of flexibility required for the SNP density isalso proposed. We illustrate the methods by application to two data sets fromthe Framingham and Six Cities Studies, and present simulations demonstratingperformance of the approach.
Download or read book A Guide to Manuscripts Relating to the History of the British Empire 1748-1776 written by and published by . This book was released on 1970 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Yin Chen
Publisher :
ISBN 13 :
Total Pages : 189 pages
Book Rating : 4.:/5 (711 download)
Download or read book Quasi-Monte Carlo Methods in Generalized Linear Mixed Model with Correlated and Non-normal Random Effects written by Yin Chen and published by . This book was released on 2009 with total page 189 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Christian Heumann
Publisher :
ISBN 13 :
Total Pages : 173 pages
Book Rating : 4.:/5 (634 download)
Download or read book Monte Carlo Methods for Missing Data in Generalized Linear and Generalized Linear Mixed Models written by Christian Heumann and published by . This book was released on 2004 with total page 173 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Cornell University. Department of Biometrics
Publisher :
ISBN 13 :
Total Pages : 292 pages
Book Rating : 4.E/5 ( download)
Download or read book Annual Report written by Cornell University. Department of Biometrics and published by . This book was released on with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Ding-Geng (Din) Chen
Publisher : Springer
ISBN 13 : 9811033072
Total Pages : 440 pages
Book Rating : 4.8/5 (11 download)
Download or read book Monte-Carlo Simulation-Based Statistical Modeling written by Ding-Geng (Din) Chen and published by Springer. This book was released on 2017-02-01 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book brings together expert researchers engaged in Monte-Carlo simulation-based statistical modeling, offering them a forum to present and discuss recent issues in methodological development as well as public health applications. It is divided into three parts, with the first providing an overview of Monte-Carlo techniques, the second focusing on missing data Monte-Carlo methods, and the third addressing Bayesian and general statistical modeling using Monte-Carlo simulations. The data and computer programs used here will also be made publicly available, allowing readers to replicate the model development and data analysis presented in each chapter, and to readily apply them in their own research. Featuring highly topical content, the book has the potential to impact model development and data analyses across a wide spectrum of fields, and to spark further research in this direction.
Author : Minjeong Jeon
Publisher :
ISBN 13 :
Total Pages : 116 pages
Book Rating : 4.:/5 (851 download)
Download or read book Monte Carlo Kernel Likelihood Method for Generalized Linear Mixed Models with Crossed Random Effects written by Minjeong Jeon and published by . This book was released on 2011 with total page 116 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : J. Hammersley
Publisher : Springer Science & Business Media
ISBN 13 : 9400958196
Total Pages : 184 pages
Book Rating : 4.4/5 (9 download)
Download or read book Monte Carlo Methods written by J. Hammersley and published by Springer Science & Business Media. This book was released on 2013-03-07 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph surveys the present state of Monte Carlo methods. we have dallied with certain topics that have interested us Although personally, we hope that our coverage of the subject is reasonably complete; at least we believe that this book and the references in it come near to exhausting the present range of the subject. On the other hand, there are many loose ends; for example we mention various ideas for variance reduction that have never been seriously appli(:d in practice. This is inevitable, and typical of a subject that has remained in its infancy for twenty years or more. We are convinced Qf:ver theless that Monte Carlo methods will one day reach an impressive maturity. The main theoretical content of this book is in Chapter 5; some readers may like to begin with this chapter, referring back to Chapters 2 and 3 when necessary. Chapters 7 to 12 deal with applications of the Monte Carlo method in various fields, and can be read in any order. For the sake of completeness, we cast a very brief glance in Chapter 4 at the direct simulation used in industrial and operational research, where the very simplest Monte Carlo techniques are usually sufficient. We assume that the reader has what might roughly be described as a 'graduate' knowledge of mathematics. The actual mathematical techniques are, with few exceptions, quite elementary, but we have freely used vectors, matrices, and similar mathematical language for the sake of conciseness.
Author : Lang Wu
Publisher : CRC Press
ISBN 13 : 9781420074086
Total Pages : 431 pages
Book Rating : 4.0/5 (74 download)
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.
Author : Jelke G. Bethlehem
Publisher : Springer Science & Business Media
ISBN 13 : 9783790813265
Total Pages : 556 pages
Book Rating : 4.8/5 (132 download)
Download or read book COMPSTAT written by Jelke G. Bethlehem and published by Springer Science & Business Media. This book was released on 2000-08-04 with total page 556 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains the keynote, invited and full contributed papers presented at COMPSTAT 2000, held in Utrecht. The papers range over all aspects of the link between statistical theory and applied statistics, with special attention for developments in the area of official statistics. The papers have been thoroughly refereed.
Author : David Ruppert
Publisher : Cambridge University Press
ISBN 13 : 9780521785167
Total Pages : 408 pages
Book Rating : 4.7/5 (851 download)
Download or read book Semiparametric Regression written by David Ruppert and published by Cambridge University Press. This book was released on 2003-07-14 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: Even experts on semiparametric regression should find something new here.
Author : Geoffrey J. McLachlan
Publisher : John Wiley & Sons
ISBN 13 : 0470191600
Total Pages : 399 pages
Book Rating : 4.4/5 (71 download)
Download or read book The EM Algorithm and Extensions written by Geoffrey J. McLachlan and published by John Wiley & Sons. This book was released on 2007-11-09 with total page 399 pages. Available in PDF, EPUB and Kindle. Book excerpt: The only single-source——now completely updated and revised——to offer a unified treatment of the theory, methodology, and applications of the EM algorithm Complete with updates that capture developments from the past decade, The EM Algorithm and Extensions, Second Edition successfully provides a basic understanding of the EM algorithm by describing its inception, implementation, and applicability in numerous statistical contexts. In conjunction with the fundamentals of the topic, the authors discuss convergence issues and computation of standard errors, and, in addition, unveil many parallels and connections between the EM algorithm and Markov chain Monte Carlo algorithms. Thorough discussions on the complexities and drawbacks that arise from the basic EM algorithm, such as slow convergence and lack of an in-built procedure to compute the covariance matrix of parameter estimates, are also presented. While the general philosophy of the First Edition has been maintained, this timely new edition has been updated, revised, and expanded to include: New chapters on Monte Carlo versions of the EM algorithm and generalizations of the EM algorithm New results on convergence, including convergence of the EM algorithm in constrained parameter spaces Expanded discussion of standard error computation methods, such as methods for categorical data and methods based on numerical differentiation Coverage of the interval EM, which locates all stationary points in a designated region of the parameter space Exploration of the EM algorithm's relationship with the Gibbs sampler and other Markov chain Monte Carlo methods Plentiful pedagogical elements—chapter introductions, lists of examples, author and subject indices, computer-drawn graphics, and a related Web site The EM Algorithm and Extensions, Second Edition serves as an excellent text for graduate-level statistics students and is also a comprehensive resource for theoreticians, practitioners, and researchers in the social and physical sciences who would like to extend their knowledge of the EM algorithm.
Author : Anders Skrondal
Publisher : CRC Press
ISBN 13 : 0203489438
Total Pages : 528 pages
Book Rating : 4.2/5 (34 download)
Download or read book Generalized Latent Variable Modeling written by Anders Skrondal and published by CRC Press. This book was released on 2004-05-11 with total page 528 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book unifies and extends latent variable models, including multilevel or generalized linear mixed models, longitudinal or panel models, item response or factor models, latent class or finite mixture models, and structural equation models. Following a gentle introduction to latent variable modeling, the authors clearly explain and contrast a wi
Author : Shein-Chung Chow
Publisher : CRC Press
ISBN 13 : 135111025X
Total Pages : 4031 pages
Book Rating : 4.3/5 (511 download)
Download or read book Encyclopedia of Biopharmaceutical Statistics - Four Volume Set written by Shein-Chung Chow and published by CRC Press. This book was released on 2018-09-03 with total page 4031 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since the publication of the first edition in 2000, there has been an explosive growth of literature in biopharmaceutical research and development of new medicines. This encyclopedia (1) provides a comprehensive and unified presentation of designs and analyses used at different stages of the drug development process, (2) gives a well-balanced summary of current regulatory requirements, and (3) describes recently developed statistical methods in the pharmaceutical sciences. Features of the Fourth Edition: 1. 78 new and revised entries have been added for a total of 308 chapters and a fourth volume has been added to encompass the increased number of chapters. 2. Revised and updated entries reflect changes and recent developments in regulatory requirements for the drug review/approval process and statistical designs and methodologies. 3. Additional topics include multiple-stage adaptive trial design in clinical research, translational medicine, design and analysis of biosimilar drug development, big data analytics, and real world evidence for clinical research and development. 4. A table of contents organized by stages of biopharmaceutical development provides easy access to relevant topics. About the Editor: Shein-Chung Chow, Ph.D. is currently an Associate Director, Office of Biostatistics, U.S. Food and Drug Administration (FDA). Dr. Chow is an Adjunct Professor at Duke University School of Medicine, as well as Adjunct Professor at Duke-NUS, Singapore and North Carolina State University. Dr. Chow is the Editor-in-Chief of the Journal of Biopharmaceutical Statistics and the Chapman & Hall/CRC Biostatistics Book Series and the author of 28 books and over 300 methodology papers. He was elected Fellow of the American Statistical Association in 1995.
Author :
Publisher :
ISBN 13 :
Total Pages : 684 pages
Book Rating : 4.3/5 (91 download)
Download or read book Journal of the American Statistical Association written by and published by . This book was released on 2004 with total page 684 pages. Available in PDF, EPUB and Kindle. Book excerpt:
