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Additive and Cancellative Interacting Particle Systems (Lecture Notes in Mathematics) by David Griffeath (Repost)
Advances in Complex Function Theory (Lecture Notes in Mathematics) by W. E. Kirwan (Repost)
Matrix Mathematics - Theory, Facts, and Formulas, Second Edition
Mathematics Probability, Markov Chains, Queues, and Simulation - The Mathematical Basis of Performance Modeling
Algebraic Aspects of Cryptography (Algorithms and Computation in Mathematics) by Neal Koblitz (Repost)
Mathematics Mathematical Foundations of Computer Science 2004 [Repost]
Mathematics Mathematical Logic for Computer Science (3rd edition)
Spaces of Holomorphic Functions in the Unit Ball (Graduate Texts in Mathematics) by Kehe Zhu (Repost)
An Introduction to Ergodic Theory (Graduate Texts in Mathematics) by Peter Walters (Repost)
Mathematics Symmetry Theory in Molecular Physics with Mathematica: A new kind of tutorial book (Repost)
-Mathematics for the Physical Sciences- by Herbert S. Wilf
Mathematics for Elementary Teachers - A Conceptual Approach, 9 edition
Computer-Enabled Mathematics - Integrating Experiment and Theory in Teacher Education
How to Fold It - The Mathematics of Linkages, Origami and Polyhedra
Mathematics Engineering Analysis: Interactive Methods and Programs with FORTRAN, QuickBASIC, MATLAB, and Mathematica [Repost]
Mathematics Maverick Mathematician: The Life and Science of J.E. Moyal
African Mathematics: From Bones to Computers (repost)
Topology (Allyn and Bacon Series in Advanced Mathematics) by James Dugundji
Mathematics Fundamentals of Algebraic Modeling - An Introduction to Mathematical Modeling with Algebra and Statistics, 5 edition
Mathematics LMSST - 24 Lectures on Elliptic Curves (London Mathematical Society Student Texts) by J. W. S. Cassels
Advances in Complex Function Theory (Lecture Notes in Mathematics) by W. E. Kirwan (Repost)
Matrix Mathematics - Theory, Facts, and Formulas, Second Edition
Mathematics Probability, Markov Chains, Queues, and Simulation - The Mathematical Basis of Performance Modeling
Algebraic Aspects of Cryptography (Algorithms and Computation in Mathematics) by Neal Koblitz (Repost)
Mathematics Mathematical Foundations of Computer Science 2004 [Repost]
Mathematics Mathematical Logic for Computer Science (3rd edition)
Spaces of Holomorphic Functions in the Unit Ball (Graduate Texts in Mathematics) by Kehe Zhu (Repost)
An Introduction to Ergodic Theory (Graduate Texts in Mathematics) by Peter Walters (Repost)
Mathematics Symmetry Theory in Molecular Physics with Mathematica: A new kind of tutorial book (Repost)
-Mathematics for the Physical Sciences- by Herbert S. Wilf
Mathematics for Elementary Teachers - A Conceptual Approach, 9 edition
Computer-Enabled Mathematics - Integrating Experiment and Theory in Teacher Education
How to Fold It - The Mathematics of Linkages, Origami and Polyhedra
Mathematics Engineering Analysis: Interactive Methods and Programs with FORTRAN, QuickBASIC, MATLAB, and Mathematica [Repost]
Mathematics Maverick Mathematician: The Life and Science of J.E. Moyal
African Mathematics: From Bones to Computers (repost)
Topology (Allyn and Bacon Series in Advanced Mathematics) by James Dugundji
Mathematics Fundamentals of Algebraic Modeling - An Introduction to Mathematical Modeling with Algebra and Statistics, 5 edition
Mathematics LMSST - 24 Lectures on Elliptic Curves (London Mathematical Society Student Texts) by J. W. S. Cassels
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Mathematics Models for Discrete Longitudinal Data
Posted on 2010-04-12
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More Geert Molenberghs, Geert Verbeke "Models for Discrete Longitudinal Data" This book provides a comprehensive treatment on modeling approaches for non-Gaussian repeated measures, possibly subject to incompleteness. The authors begin with models for the full marginal distribution of the outcome vector. This allows model fitting to be based on maximum likelihood principles, immediately implying inferential tools for all parameters in the models. At the same time, they formulate computationally less complex alternatives, including generalized estimating equations and pseudo-likelihood methods. They then briefly introduce conditional models and move on to the random-effects family, encompassing the beta-binomial model, the probit model and, in particular the generalized linear mixed model. Several frequently used procedures for model fitting are discussed and differences between marginal models and random-effects models are given attention. The authors consider a variety of extensions, such as models for multivariate longitudinal measurements, random-effects models with serial correlation, and mixed models with non-Gaussian random effects. They sketch the general principles for how to deal with the commonly encountered issue of incomplete longitudinal data. The authors critique frequently used methods and propose flexible and broadly valid methods instead, and conclude with key concepts of sensitivity analysis. Without putting too much emphasis on software, the book shows how the different approaches can be implemented within the SAS software package. The text is organized so that the reader can skip the software-oriented chapters and sections without breaking the logical flow. From the reviews: "Strengths of this book include its breadth of topics, excellent organization and clarity of writing...I highly recommend this book to my colleagues and students." -Justine Shults for the Journal of Biopharmaceutical Statistics, Issue 3, 2006 "Models for Discrete Longitudinal Data is an excellent choice for any statistician with an interest in analyzing discrete longitudinal data. It covers all of the theoretical and applied aspects in this area and is organized in such a way to serve as a handy reference guide for applied statisticians, especially those in biomedical fields. I learned a great deal from this book, and I recommend it highly to others." -John Williamson for the Journal of the American Statistical Association, September 2006
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