Random Effect and Latent Variable Model Selection (Record no. 38510)

MARC details
000 -LEADER
fixed length control field 04062n a2200385#a 4500
001 - CONTROL NUMBER
control field 5000083
003 - CONTROL NUMBER IDENTIFIER
control field DE-He213
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20221213140638.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr||||||||||||
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 100317s2008 xxu| s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9780387767215
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1007/978-0-387-76721-5
Source of number or code doi
035 ## - SYSTEM CONTROL NUMBER
System control number 978-0-387-76721-5
072 #7 - SUBJECT CATEGORY CODE
Subject category code PBT
Source bicssc
072 #7 - SUBJECT CATEGORY CODE
Subject category code MAT029000
Source bisacsh
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 519.5
090 ## - IMPA CODE FOR CLASSIFICATION SHELVES
IMPA CODE FOR CLASSIFICATION SHELVES Matemáticas Gerais-(inclusive alguns textos elementares sobre assuntos específicos)
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Dunson, David B.
9 (RLIN) 9318
245 10 - TITLE STATEMENT
Title Random Effect and Latent Variable Model Selection
Medium [electronic resource]/
Statement of responsibility, etc. edited by David B. Dunson.
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. New York:
Name of publisher, distributor, etc. Springer New York:
-- Springer,
Date of publication, distribution, etc. 2008.
300 ## - PHYSICAL DESCRIPTION
Extent X, 174p.
Other physical details digital.
490 0# - SERIES STATEMENT
Series statement Lecture Notes in Statistics,
International Standard Serial Number 0930-0325;
Volume/sequential designation 192
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Ciprian Crainiceanu, Likelihood ratio tests for inference on variance components in random effects models -- Xihong Lin, Variance component testing in generalized linear models with random effects -- Dongchu Sun, Priors for variance component testing -- Jiming Jiang, Frequentist subset selection in random effects models -- David Dunson and Saki Kinney, Bayesian variable selection in linear and logistic mixed effects models -- Bo Cai and David Dunson, Bayesian variable selection in generalized linear mixed models -- Peter Bentler, Model comparison in structural equation models -- Ken Bollen and Surajit Ray, Bayesian model selection criteria for hierarchical and structural equation models -- Sik-Yum Lee, Comparing structural equation models using Bayes factors .
520 ## - SUMMARY, ETC.
Summary, etc. Random effects and latent variable models are broadly used in analyses of multivariate data. These models can accommodate high dimensional data having a variety of measurement scales. Methods for model selection and comparison are needed in conducting hypothesis tests and in building sparse predictive models. However, classical methods for model comparison are not well justified in such settings. This book presents state of the art methods for accommodating model uncertainty in random effects and latent variable models. It will appeal to students, applied data analysts, and experienced researchers. The chapters are based on the contributors’ research, with mathematical details minimized using applications-motivated descriptions. The first part of the book focuses on frequentist likelihood ratio and score tests for zero variance components. Contributors include Xihong Lin, Daowen Zhang and Ciprian Crainiceanu. The second part focuses on Bayesian methods for random effects selection in linear mixed effects and generalized linear mixed models. Contributors include David Dunson and collaborators Bo Cai and Saki Kinney. The final part focuses on structural equation models, with Peter Bentler and Jiajuan Liang presenting a frequentist approach, Sik-Yum Lee and Xin-Yuan Song presenting a Bayesian approach based on path sampling, and Joyee Ghosh and David Dunson proposing a method for default prior specification and efficient posterior computation. David Dunson is Professor in the Department of Statistical Science at Duke University. He is an international authority on Bayesian methods for correlated data, a fellow of the American Statistical Association, and winner of the David Byar and Mortimer Spiegelman Awards .
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Statistics.
9 (RLIN) 43790
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Mathematical statistics
9 (RLIN) 43558
697 ## - LOCAL SUBJECT
Local Subject Matemáticas Gerais-
Description subdivision (inclusive alguns textos elementares sobre assuntos específicos)
Linkage 23752
710 1# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service).
9 (RLIN) 8857
773 0# - HOST ITEM ENTRY
Title Springer eBooks
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Relationship information Printed edition:
International Standard Book Number 9780387767208
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title Lecture notes in statistics (Springer-Verlag);
Volume/sequential designation 192
9 (RLIN) 44238
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="http://dx.doi.org/10.1007/978-0-387-76721-5">http://dx.doi.org/10.1007/978-0-387-76721-5</a>
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Instituto de Matemática Pura e Aplicada
Koha item type E-Book

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