***Winner of the 2008 Ziegel Prize for outstanding new book of the
year***
Structural equation modeling (SEM) is a powerful multivariate
method allowing the evaluation of a series of simultaneous
hypotheses about the impacts of latent and manifest variables on
other variables, taking measurement errors into account. As SEMs
have grown in popularity in recent years, new models and
statistical methods have been developed for more accurate analysis
of more complex data. A Bayesian approach to SEMs allows the use of
prior information resulting in improved parameter estimates, latent
variable estimates, and statistics for model comparison, as well as
offering more reliable results for smaller samples.
"Structural Equation Modeling" introduces the Bayesian approach
to SEMs, including the selection of prior distributions and data
augmentation, and offers an overview of the subject's recent
advances.
Demonstrates how to utilize powerful statistical computing
tools, including the Gibbs sampler, the Metropolis-Hasting
algorithm, bridge sampling and path sampling to obtain the Bayesian
results.Discusses the Bayes factor and Deviance Information
Criterion (DIC) for model comparison.Includes coverage of complex
models, including SEMs with ordered categorical variables, and
dichotomous variables, nonlinear SEMs, two-level SEMs, multisample
SEMs, mixtures of SEMs, SEMs with missing data, SEMs with variables
from an exponential family of distributions, and some of their
combinations.Illustrates the methodology through simulation studies
and examples with real data from business management, education,
psychology, public health and sociology.Demonstrates the
application of the freely available software WinBUGS via a
supplementary website featuring computer code and data sets.
"Structural Equation Modeling: A Bayesian Approach" is a
multi-disciplinary text ideal for researchers and students in many
areas, including: statistics, biostatistics, business, education,
medicine, psychology, public health and social science.
General
Imprint: |
John Wiley & Sons
|
Country of origin: |
United States |
Series: |
Wiley Series in Probability and Statistics |
Release date: |
2007 |
First published: |
March 2007 |
Authors: |
Sik--Yum Lee
|
Dimensions: |
229 x 152 x 26mm (L x W x T) |
Format: |
Hardcover
|
Pages: |
458 |
ISBN-13: |
978-0-470-02423-2 |
Categories: |
Books >
Science & Mathematics >
Mathematics >
Probability & statistics
|
LSN: |
0-470-02423-2 |
Barcode: |
9780470024232 |
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