New Developments and Techniques in Structural Equation Modeling

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advanced SEM methods for health sciences
BIC Value
categorical
Category=JHBC
Category=PBT
CFA Study
covariance
Covariance Matrix
Data Sets
eq_bestseller
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_society-politics
Equivalent Models
Error Covariance
Exogenous Latent Variables
factor
Factor Loading Matrices
Full Conditional
Full Conditional Distribution
genetic algorithm optimization
growth
Growth Mixture Modeling
Intra-class Correlation
Intraclass Correlation
Item Parceling
item parceling techniques
latent
Latent Class
latent variable analysis
Latent Variables
matrix
measurement
mixture
multilevel
Multilevel Factor Model
Multilevel SEM
multilevel statistical modeling
Nonstandard Samples
randomized trial methodology
Raw Data
robust error estimation
SEM Framework
Structural Equation Modeling
Time Specific Residuals
Unbalanced Group Sizes
Univariate Growth Model
variable

Product details

  • ISBN 9780805835939
  • Weight: 680g
  • Dimensions: 152 x 229mm
  • Publication Date: 01 Mar 2001
  • Publisher: Taylor & Francis Inc
  • Publication City/Country: US
  • Product Form: Hardback
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Featuring contributions from some of the leading researchers in the field of SEM, most chapters are written by the author(s) who originally proposed the technique and/or contributed substantially to its development. Content highlights include latent variable mixture modeling, multilevel modeling, interaction modeling, models for dealing with nonstandard and noncompliance samples, the latest on the analysis of growth curve and longitudinal data, specification searches, item parceling, and equivalent models. This volume will appeal to educators, psychologists, biologists, business professionals, medical researchers, and other social and health scientists. It is assumed that the reader has mastered the equivalent of a graduate-level multivariate statistics course that included coverage of introductory SEM techniques.

George A. Marcoulides, Randall E. Schumacker