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Missing Data
intercepts do not have to appear in the model unless you want to estimate them or
constrain them.
The fit of Model A is summarized as follows:
The Function of log likelihood value is displayed instead of the chi-square fit statistic
that you get with complete data. In addition, at the beginning of the Summary of models
section of the text output, Amos displays the warning:
Whenever Amos prints this note, the values in the cmin column of the Summary of
models
section do not contain the familiar fit chi-square statistics. To evaluate the fit
of the factor model, its Function of log likelihood value has to be compared to that of
some less constrained baseline model, such as the saturated model.
Fitting the Saturated Model (Model B)
The saturated model has as many free parameters as there are first and second order
moments. When complete data are analyzed, the saturated model always fits the
sample data perfectly (with chi-square = 0.00 and df = 0). All structural equation
models with the same six observed variables are either equivalent to the saturated
model or are constrained versions of it. A saturated model will fit the sample data at
least as well as any constrained model, and its Function of log likelihood value will be
no larger and is, typically, smaller.
Function of log likelihood = 1375.133
Number of parameters = 19
The saturated model was not fitted to the data of at least one group. For this
reason, only the 'function of log likelihood', AIC and BCC are reported. The
likelihood ratio chi-square statistic and other fit measures are not reported.