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Example 17
This section outlines three steps necessary for computing the likelihood ratio chi-
square statistic:
Fitting the factor model
Fitting the saturated model
Computing the likelihood ratio chi-square statistic and its p value
First, the three steps are performed by three separate programs. After that, the three
steps will be combined into a single program.
Fitting the Factor Model (Model A)
The following program fits the confirmatory factor model (Model A). It is saved as
Ex17-a.vb.
Notice that the
ModelMeansAndIntercepts method is used to specify that means and
intercepts are parameters of the model, and that each of the six regression equations
contains a set of empty parentheses representing an intercept. When you analyze data
with missing values, means and intercepts must appear in the model as explicit
parameters. This is different from the analysis of complete data, where means and
Sub Main()
Dim Sem As New AmosEngine
Try
Sem.Title("Example 17 a: Factor Model")
Sem.TextOutput()
Sem.Standardized()
Sem.Smc()
Sem.AllImpliedMoments()
Sem.ModelMeansAndIntercepts()
Sem.BeginGroup(Sem.AmosDir & "Examples\Grant_x.sav")
Sem.AStructure("visperc = ( ) + (1) spatial + (1) err_v")
Sem.AStructure("cubes = ( ) + spatial + (1) err_c")
Sem.AStructure("lozenges = ( ) + spatial + (1) err_l")
Sem.AStructure("paragrap = ( ) + (1) verbal + (1) err_p")
Sem.AStructure("sentence = ( ) + verbal + (1) err_s")
Sem.AStructure("wordmean = ( ) + verbal + (1) err_w")
Sem.FitModel()
Finally
Sem.Dispose()
End Try
End Sub