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Mixture Modeling with Training Data
Latent Structure Analysis
It was mentioned earlier that you are not limited to saturated models when doing
mixture modeling. You can use a factor analysis model, a regression model, or any
model at all. You may want to become familiar with an important variation of the
saturated model. Latent structure analysis (Lazarsfeld and Henry, 1968) is a variation
of mixture modeling in which the measured variables are required to be independent
within each group. When the measured variables are multivariate normal, they are
required to be uncorrelated.
E To require that the measured variables be uncorrelated, delete the double-headed arrow
in the path diagram of the saturated model. (This path diagram is saved as Ex34-
b.amw.)
E Click the Bayesian button to perform the latent structure analysis. The results of the
latent structure analysis will not be presented here.
