Modeling Interaction Effects in Latent Growth Curve Models
By Fuzhong Li, Terry E. Duncan, A. Acock. 2000
51 citations recorded by the source corpus.
This article presents an extension of Jöreskog and Yang's (1996) method of estimating interaction effects among latent variables to latent growth curve models. Models involving a product of 2 latent factors of either static or dynamic variables (parental monitoring and rule-setting) predicting an outcome growth variable (adolescents' initial status and rate of change in antisocial behavior) are used as substantive illustrations. The results are discussed in terms of practical and statistical problems associated with interaction analyses in latent curve models, and in structural equation models with latent variables in general.
Subfields: Clinical Psychology, Education, Sociology and Political Science
View Paper: https://www.semanticscholar.org/paper/e885c4fd71e064e5bc48a0202f5e1867c2208a19
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In Education
In Sociology and Political Science
Citations in the corpus
- Comparison of Inverse Wishart and Separation-Strategy Priors for Bayesian Estimation of Covariance Parameter Matrix in Growth Curve Analysis (2016, background): “…Lee, and Hser (2009) proposed a growth curve model for studying both the dynamic change of multivariate manifest variables and latent variables; Li, Duncan, and Acock (2000) investigated a growth curve model with interaction effects, and Cai, Song, and Lee (2008) studied a growth curve model…”