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9781118358887
(electronic bk.)
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519.5/3
519.53
MAT029000
bisacsh
MAIN
Song, Xin-Yuan.
Basic and advanced Bayesian structural equation modeling :
with applications in the medical and behavioral sciences /
Xin-Yuan Song and Sik-Yum Lee.
Chichester, West Sussex :
John Wiley & Sons,
2012.
1 online resource (xvii, 367 pages) :
illustrations.
text
txt
rdacontent
computer
c
rdamedia
online resource
cr
rdacarrier
Wiley series in probability and statistics
Includes bibliographical references and index.
Introduction -- Basic concepts and applications of structural equation models -- Bayesian methods for estimating structural equation models -- Bayesian model comparison and model checking -- Practical structural equation models -- Structural equation models with hierarchical and multisample data -- Mixture structural equation models -- Structural equation modeling for latent curve models -- Longitudinal structural equation models -- Semiparametric structural equation models with continuous variables -- Structural equation models with mixed continuous and unordered categorical variables -- Structural equation models with nonparametric structural equations -- Transformation structural equation models -- Conclusion.
"This book provides clear instructions to researchers on how to apply Structural Equation Models (SEMs) for analyzing the inter relationships between observed and latent variables. Basic and Advanced Bayesian Structural Equation Modeling introduces basic and advanced SEMs for analyzing various kinds of complex data, such as ordered and unordered categorical data, multilevel data, mixture data, longitudinal data, highly non-normal data, as well as some of their combinations. In addition, Bayesian semiparametric SEMs to capture the true distribution of explanatory latent variables are introduced, whilst SEM with a nonparametric structural equation to assess unspecified functional relationships among latent variables are also explored. Statistical methodologies are developed using the Bayesian approach giving reliable results for small samples and allowing the use of prior information leading to better statistical results. Estimates of the parameters and model comparison statistics are obtained via powerful Markov Chain Monte Carlo methods in statistical computing."--Publisher's website.
Print version record.
Bayesian statistical decision theory.
Structural equation modeling.
Mathematics.
Bayesian statistical decision theory.
fast
(OCoLC)fst00829019
Structural equation modeling.
fast
(OCoLC)fst01738928
Electronic books.
Lee, Sik-Yum.
Print version:
Song, Xin-Yuan.
Basic and advanced Bayesian structural equation modeling.
Chichester, West Sussex : John Wiley, 2012
9780470669525
(DLC) 2012012199
(OCoLC)853461614
Wiley series in probability and statistics.
http://dx.doi.org/10.1002/9781118358887
Wiley Online Library
92
DG1
19580
19539