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Random Effect And Latent Variable Model Selection

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Random Effect And Latent Variable Model Selection

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Author : David Dunson
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-03-18

Random Effect And Latent Variable Model Selection written by David Dunson 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 2010-03-18 with Mathematics categories.

Random Effect and Latent Variable Model Selection In recent years, there has been a dramatic increase in the collection of multivariate and correlated data in a wide variety of ?elds. For example, it is now standard pr- tice to routinely collect many response variables on each individual in a study. The different variables may correspond to repeated measurements over time, to a battery of surrogates for one or more latent traits, or to multiple types of outcomes having an unknown dependence structure. Hierarchical models that incorporate subje- speci?c parameters are one of the most widely-used tools for analyzing multivariate and correlated data. Such subject-speci?c parameters are commonly referred to as random effects, latent variables or frailties. There are two modeling frameworks that have been particularly widely used as hierarchical generalizations of linear regression models. The ?rst is the linear mixed effects model (Laird and Ware , 1982) and the second is the structural equation model (Bollen , 1989). Linear mixed effects (LME) models extend linear regr- sion to incorporate two components, with the ?rst corresponding to ?xed effects describing the impact of predictors on the mean and the second to random effects characterizing the impact on the covariance. LMEs have also been increasingly used for function estimation. In implementing LME analyses, model selection problems are unavoidable. For example, there may be interest in comparing models with and without a predictor in the ?xed and/or random effects component.

Random Effect And Latent Variable Model Selection

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Author : David Dunson
language : en
Publisher: Springer
Release Date : 2010-11-16

Random Effect And Latent Variable Model Selection written by David Dunson and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-11-16 with Mathematics categories.

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

Generalized Latent Variable Modeling

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Author : Anders Skrondal
language : en
Publisher: CRC Press
Release Date : 2004-05-11

Generalized Latent Variable Modeling written by Anders Skrondal and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-05-11 with Mathematics categories.

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 wide range of estimation and prediction methods from biostatistics, psychometrics, econometrics, and statistics. They present exciting and realistic applications that demonstrate how researchers can use latent variable modeling to solve concrete problems in areas as diverse as medicine, economics, and psychology. The examples considered include many nonstandard response types, such as ordinal, nominal, count, and survival data. Joint modeling of mixed responses, such as survival and longitudinal data, is also illustrated. Numerous displays, figures, and graphs make the text vivid and easy to read. About the authors: Anders Skrondal is Professor and Chair in Social Statistics, Department of Statistics, London School of Economics, UK Sophia Rabe-Hesketh is a Professor of Educational Statistics at the Graduate School of Education and Graduate Group in Biostatistics, University of California, Berkeley, USA.

Applied Bayesian Hierarchical Methods

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Author : Peter D. Congdon
language : en
Publisher: CRC Press
Release Date : 2010-05-19

Applied Bayesian Hierarchical Methods 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 2010-05-19 with Mathematics categories.

The use of Markov chain Monte Carlo (MCMC) methods for estimating hierarchical models involves complex data structures and is often described as a revolutionary development. An intermediate-level treatment of Bayesian hierarchical models and their applications, Applied Bayesian Hierarchical Methods demonstrates the advantages of a Bayesian approach

Handbook Of Item Response Theory

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Author : Wim J. van der Linden
language : en
Publisher: CRC Press
Release Date : 2017-03-31

Handbook Of Item Response Theory written by Wim J. van der Linden and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-31 with Mathematics categories.

Drawing on the work of internationally acclaimed experts in the field, Handbook of Item Response Theory, Volume Two: Statistical Tools presents classical and modern statistical tools used in item response theory (IRT). While IRT heavily depends on the use of statistical tools for handling its models and applications, systematic introductions and reviews that emphasize their relevance to IRT are hardly found in the statistical literature. This second volume in a three-volume set fills this void. Volume Two covers common probability distributions, the issue of models with both intentional and nuisance parameters, the use of information criteria, methods for dealing with missing data, and model identification issues. It also addresses recent developments in parameter estimation and model fit and comparison, such as Bayesian approaches, specifically Markov chain Monte Carlo (MCMC) methods.

Multilevel Modeling

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Author : G. David Garson
language : en
Publisher: SAGE Publications
Release Date : 2019-07-31

Multilevel Modeling written by G. David Garson and has been published by SAGE Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-31 with Education categories.

Multilevel Modeling: Applications in STATA®, IBM® SPSS®, SAS®, R & HLMTM provides a gentle, hands-on illustration of the most common types of multilevel modeling software, offering instructors multiple software resources for their students and an applications-based foundation for teaching multilevel modeling in the social sciences. Author G. David Garson’s step-by-step instructions for software walk readers through each package. The instructions for the different platforms allow students to get a running start using the package with which they are most familiar while the instructor can start teaching the concepts of multilevel modeling right away. Instructors will find this text serves as both a comprehensive resource for their students and a foundation for their teaching alike.

Current Trends In Bayesian Methodology With Applications

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Author : Satyanshu K. Upadhyay
language : en
Publisher: CRC Press
Release Date : 2015-05-21

Current Trends In Bayesian Methodology With Applications written by Satyanshu K. Upadhyay and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-05-21 with Mathematics categories.

Collecting Bayesian material scattered throughout the literature, Current Trends in Bayesian Methodology with Applications examines the latest methodological and applied aspects of Bayesian statistics. The book covers biostatistics, econometrics, reliability and risk analysis, spatial statistics, image analysis, shape analysis, Bayesian computation, clustering, uncertainty assessment, high-energy astrophysics, neural networking, fuzzy information, objective Bayesian methodologies, empirical Bayes methods, small area estimation, and many more topics. Each chapter is self-contained and focuses on a Bayesian methodology. It gives an overview of the area, presents theoretical insights, and emphasizes applications through motivating examples. This book reflects the diversity of Bayesian analysis, from novel Bayesian methodology, such as nonignorable response and factor analysis, to state-of-the-art applications in economics, astrophysics, biomedicine, oceanography, and other areas. It guides readers in using Bayesian techniques for a range of statistical analyses.

Bayesian Disease Mapping

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Author : Andrew B. Lawson
language : en
Publisher: CRC Press
Release Date : 2018-05-20

Bayesian Disease Mapping written by Andrew B. Lawson and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-20 with Mathematics categories.

Since the publication of the second edition, many new Bayesian tools and methods have been developed for space-time data analysis, the predictive modeling of health outcomes, and other spatial biostatistical areas. Exploring these new developments, Bayesian Disease Mapping: Hierarchical Modeling in Spatial Epidemiology, Third Edition provides an up-to-date, cohesive account of the full range of Bayesian disease mapping methods and applications. In addition to the new material, the book also covers more conventional areas such as relative risk estimation, clustering, spatial survival analysis, and longitudinal analysis. After an introduction to Bayesian inference, computation, and model assessment, the text focuses on important themes, including disease map reconstruction, cluster detection, regression and ecological analysis, putative hazard modeling, analysis of multiple scales and multiple diseases, spatial survival and longitudinal studies, spatiotemporal methods, and map surveillance. It shows how Bayesian disease mapping can yield significant insights into georeferenced health data. The target audience for this text is public health specialists, epidemiologists, and biostatisticians who need to work with geo-referenced health data.

Medical Statistics

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Author : Filomena Pereira-Maxwell
language : en
Publisher: CRC Press
Release Date : 2018-05-15

Medical Statistics written by Filomena Pereira-Maxwell and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-15 with Medical categories.

Clear and user-friendly A-Z format, in handy a pocket size, allows speedy access to information in all settings Fully updated and expanded to cover over 500 statistical terms for comprehensive coverage Enhanced explanations of statistical concepts and methods, including more illustrative content, for greater accessibility Frequent use of examples from the medical literature, with reference to landmark studies, ensures clinical relevance Those new to medical statistics and the more experienced reader will find something of interest here

Random Effect And Latent Variable Model Selection

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