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Koran, Jennifer; Hancock, Gregory R. – Structural Equation Modeling: A Multidisciplinary Journal, 2010
Valuable methods have been developed for incorporating ordinal variables into structural equation models using a latent response variable formulation. However, some model parameters, such as the means and variances of latent factors, can be quite difficult to interpret because the latent response variables have an arbitrary metric. This limitation…
Descriptors: Structural Equation Models, Data, Classification, Reading
Hancock, Gregory R.; Choi, Jaehwa – Structural Equation Modeling: A Multidisciplinary Journal, 2006
In its most basic form, latent growth modeling (latent curve analysis) allows an assessment of individuals' change in a measured variable X over time. For simple linear models, as with other growth models, parameter estimates associated with the a construct (amount of X at a chosen temporal reference point) and b construct (growth in X per unit…
Descriptors: Structural Equation Models, Item Response Theory, Statistical Analysis, Research Methodology

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