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Example 4
E Draw three double-headed arrows that connect the observed exogenous variables
(knowledge, satisfaction, and value).
Your path diagram should look like this:
Identification
In this example, it is impossible to estimate the regression weight for the regression of
performance on error, and, at the same time, estimate the variance of error. It is like
having someone tell you, “I bought $5 worth of widgets,” and attempting to infer both
the price of each widget and the number of widgets purchased. There is just not enough
information.
You can solve this identification problem by fixing either the regression weight
applied to error in predicting performance, or the variance of the error variable itself,
at an arbitrary, nonzero value. Let’s fix the regression weight at 1. This will yield the
same estimates as conventional linear regression.
Fixing Regression Weights
E Right-click the arrow that points from error to performance and choose Object Properties
from the pop-up menu.
E Click the Parameters tab.
E Type 1 in the Regression weight box.