Longitudinal Structural Equation Modeling with Mplus

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A01=Christian Geiser
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Author_Christian Geiser
automatic-update
Bayesian estimation
Category1=Non-Fiction
Category=JMA
Category=JMB
CFA
confirmatory factor analysis
COP=United States
Delivery_Delivery within 10-20 working days
dynamic
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eq_nobargain
eq_non-fiction
eq_society-politics
growth models
intensive longitudinal data
intensive longitudinal data modelling
Language_English
latent state models
latent variables
longitudinal analysis
LST theory
maximum likelihood estimation
measurement equivalence
measurement equivalence testing
measurement models
multivariate analysis
PA=Available
Price_€50 to €100
PS=Active
psychometrics
random intercept model
repeated measures
SEM
simplex model
softlaunch
statistical software programs
texts
trait state error
using Mplus

Product details

  • ISBN 9781462544240
  • Weight: 710g
  • Dimensions: 156 x 234mm
  • Publication Date: 04 Nov 2020
  • Publisher: Guilford Publications
  • Publication City/Country: US
  • Product Form: Hardback
  • Language: English
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An in-depth guide to executing longitudinal confirmatory factor analysis (CFA) and structural equation modeling (SEM) in Mplus, this book uses latent state–trait (LST) theory as a unifying conceptual framework, including the relevant coefficients of consistency, occasion specificity, and reliability. Following a standard format, chapters review the theoretical underpinnings, strengths, and limitations of the various models; present data examples; and demonstrate each model's application and interpretation in Mplus, with numerous screen shots and output excerpts. Coverage encompasses both traditional models (autoregressive, change score, and growth curve models) and LST models for analyzing single- and multiple-indicator data. The book discusses measurement equivalence testing, intensive longitudinal data modeling, and missing data handling, and provides strategies for model selection and reporting of results. User-friendly features include special-topic boxes, chapter summaries, and suggestions for further reading. The companion website features data sets, annotated syntax files, and output for all of the examples.

Christian Geiser, PhD, is a former professor of quantitative psychology. He currently works as an instructor and statistical consultant. His areas of expertise are in structural equation modeling, longitudinal data analysis, latent class modeling, multitrait–multimethod analysis, and measurement. His website is https://christiangeiser.com/.

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