Posterior Simulation And Model Choice In Longitudinal Generalized Linear Models
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Posterior Simulation And Model Choice In Longitudinal Generalized Linear Models
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Author : Siddhartha Chib
language : en
Publisher:
Release Date : 1996
Posterior Simulation And Model Choice In Longitudinal Generalized Linear Models written by Siddhartha Chib and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996 with Linear programming categories.
Posterior Simulation And Model Choice In Longitudinal Generalized Linear Models
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Author : Siddhartha Chib
language : en
Publisher:
Release Date : 1998
Posterior Simulation And Model Choice In Longitudinal Generalized Linear Models written by Siddhartha Chib and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998 with categories.
This paper is concerned with the problems of posterior simulation and model choice for Poisson panel data models with multiple random effects. Efficient algorithms based on Markov Chain Monte Carlo methods for sampling the posterior distribution are developed. A new parameterization of the random effects and fixed effects is proposed and compared with a parameterization in common use. Computation of marginal likelihoods and Bayes factors from the simulation output is also considered. The methods are illustrated with several real data applications involving large samples and multiple random effects.
Generalized Linear Models
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Author : Dipak K. Dey
language : en
Publisher: CRC Press
Release Date : 2000-05-25
Generalized Linear Models written by Dipak K. Dey and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-05-25 with Mathematics categories.
This volume describes how to conceptualize, perform, and critique traditional generalized linear models (GLMs) from a Bayesian perspective and how to use modern computational methods to summarize inferences using simulation. Introducing dynamic modeling for GLMs and containing over 1000 references and equations, Generalized Linear Models considers parametric and semiparametric approaches to overdispersed GLMs, presents methods of analyzing correlated binary data using latent variables. It also proposes a semiparametric method to model link functions for binary response data, and identifies areas of important future research and new applications of GLMs.
Methods And Applications Of Longitudinal Data Analysis
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Author : Xian Liu
language : en
Publisher: Elsevier
Release Date : 2015-09-01
Methods And Applications Of Longitudinal Data Analysis written by Xian Liu and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-09-01 with Mathematics categories.
Methods and Applications of Longitudinal Data Analysis describes methods for the analysis of longitudinal data in the medical, biological and behavioral sciences. It introduces basic concepts and functions including a variety of regression models, and their practical applications across many areas of research. Statistical procedures featured within the text include: - descriptive methods for delineating trends over time - linear mixed regression models with both fixed and random effects - covariance pattern models on correlated errors - generalized estimating equations - nonlinear regression models for categorical repeated measurements - techniques for analyzing longitudinal data with non-ignorable missing observations Emphasis is given to applications of these methods, using substantial empirical illustrations, designed to help users of statistics better analyze and understand longitudinal data. Methods and Applications of Longitudinal Data Analysis equips both graduate students and professionals to confidently apply longitudinal data analysis to their particular discipline. It also provides a valuable reference source for applied statisticians, demographers and other quantitative methodologists. - From novice to professional: this book starts with the introduction of basic models and ends with the description of some of the most advanced models in longitudinal data analysis - Enables students to select the correct statistical methods to apply to their longitudinal data and avoid the pitfalls associated with incorrect selection - Identifies the limitations of classical repeated measures models and describes newly developed techniques, along with real-world examples.
The Sage Handbook Of Multilevel Modeling
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Author : Marc A. Scott
language : en
Publisher: SAGE
Release Date : 2013-08-31
The Sage Handbook Of Multilevel Modeling written by Marc A. Scott and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-08-31 with Reference categories.
In this important new Handbook, the editors have gathered together a range of leading contributors to introduce the theory and practice of multilevel modeling. The Handbook establishes the connections in multilevel modeling, bringing together leading experts from around the world to provide a roadmap for applied researchers linking theory and practice, as well as a unique arsenal of state-of-the-art tools. It forges vital connections that cross traditional disciplinary divides and introduces best practice in the field. Part I establishes the framework for estimation and inference, including chapters dedicated to notation, model selection, fixed and random effects, and causal inference. Part II develops variations and extensions, such as nonlinear, semiparametric and latent class models. Part III includes discussion of missing data and robust methods, assessment of fit and software. Part IV consists of exemplary modeling and data analyses written by methodologists working in specific disciplines. Combining practical pieces with overviews of the field, this Handbook is essential reading for any student or researcher looking to apply multilevel techniques in their own research.
Econometric Analysis Of Count Data
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Author : Rainer Winkelmann
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-11-27
Econometric Analysis Of Count Data written by Rainer Winkelmann 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 2013-11-27 with Business & Economics categories.
This monograph deals with econometric models for the analysis of event counts. The interest of econometricians in this class of models has started in the mid-eighties. After more than one decade of intensive research, the litera ture has reached a level of maturity that calls for a systematic and accessible exposition of the main results and methods. Such an exposition is the aim of the book. Count data models have found their way into the curricula of micro-econometric classes and are available on standard computer software. The basic methods have been used in countless applications in fields such as labor economics, health economics, insurance economics, urban economics, and economic demography, to name but a few. Other, more recent, methods are poised to become standard tools soon. While the book is oriented towards the empirical economists and applied econometrician, it should be useful to statisticians and biometricians as well. A first edition of this book was published in 1994 under the title "Count Data Models - Econometric Theory and an Application to Labor Mobility" . While this edition keeps the character and broad organization of this first edition, and its emphasis on combining a summary of the existing literature with several new results and methods, it is substantially revised and enlarged. Many parts have been completely rewritten and several new sections have New sections include: count data models for dependent processes; been added.
Bayesian Econometric Methods
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Author : Joshua Chan
language : en
Publisher: Cambridge University Press
Release Date : 2019-08-15
Bayesian Econometric Methods written by Joshua Chan 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 2019-08-15 with Business & Economics categories.
Illustrates Bayesian theory and application through a series of exercises in question and answer format.
Bayesian Hierarchical Models
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Author : Peter D. Congdon
language : en
Publisher: CRC Press
Release Date : 2019-09-16
Bayesian Hierarchical Models written by Peter D. Congdon and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-16 with Mathematics categories.
An intermediate-level treatment of Bayesian hierarchical models and their applications, this book demonstrates the advantages of a Bayesian approach to data sets involving inferences for collections of related units or variables, and in methods where parameters can be treated as random collections. Through illustrative data analysis and attention to statistical computing, this book facilitates practical implementation of Bayesian hierarchical methods. The new edition is a revision of the book Applied Bayesian Hierarchical Methods. It maintains a focus on applied modelling and data analysis, but now using entirely R-based Bayesian computing options. It has been updated with a new chapter on regression for causal effects, and one on computing options and strategies. This latter chapter is particularly important, due to recent advances in Bayesian computing and estimation, including the development of rjags and rstan. It also features updates throughout with new examples. The examples exploit and illustrate the broader advantages of the R computing environment, while allowing readers to explore alternative likelihood assumptions, regression structures, and assumptions on prior densities. Features: Provides a comprehensive and accessible overview of applied Bayesian hierarchical modelling Includes many real data examples to illustrate different modelling topics R code (based on rjags, jagsUI, R2OpenBUGS, and rstan) is integrated into the book, emphasizing implementation Software options and coding principles are introduced in new chapter on computing Programs and data sets available on the book’s website
Hierarchical Modelling Of Discrete Longitudinal Data
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Author : Leonhard Held
language : en
Publisher: Herbert Utz Verlag
Release Date : 1997
Hierarchical Modelling Of Discrete Longitudinal Data written by Leonhard Held and has been published by Herbert Utz Verlag this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997 with Longitudinal method categories.
Multilevel And Longitudinal Modeling Using Stata Second Edition
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Author : Sophia Rabe-Hesketh
language : en
Publisher: Stata Press
Release Date : 2008-02-07
Multilevel And Longitudinal Modeling Using Stata Second Edition written by Sophia Rabe-Hesketh and has been published by Stata Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-02-07 with Computers categories.
This textbook looks specifically at Stata's treatment of generalized linear mixed models, also known as multilevel or hierarchical models. These models are "mixed" because they allow fixed and random effects, and they are "generalized" because they are appropriate for continuous Gaussian responses as well as binary, count, and other types of limited dependent variables.