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Mixture Modeling without Training Data
was not necessary to click Group Value to specify a value for the grouping variable. The
data file contains no values for the grouping variable (Species), so the program
automatically constructed the following Species values for the three groups: Cluster1,
Cluster2, and Cluster3.
E Click OK to close the Data Files dialog box.
Specifying the Model
We will use a saturated model for the variables PetalLength and PetalWidth. The
scatterplot in Example 34 suggests that these two variables will allow the program to
do a good job of classifying the flowers according to species.
Note that you are not limited to saturated models when doing mixture modeling.
You can use a factor analysis model, a regression model, or any other kind of model.
Example 36 demonstrates mixture modeling with a regression model.
E Draw the following path diagram:
E From the menus, choose View > Analysis Properties.
E Select Estimate means and intercepts (a check mark will appear next to it).