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Regression with an Explicit Intercept
Notice the string 0, displayed above the error variable. The 0 to the left of the comma
indicates that the mean of the error variable is fixed at 0, a standard assumption in
linear regression models. The absence of anything to the right of the comma in 0,
means that the variance of error is not fixed at a constant and does not have a name.
With a check mark next to
Estimate means and intercepts, Amos will estimate a mean
for each of the predictors, and an intercept for the regression equation that predicts
performance.
Results of the Analysis
Text Output
The present analysis gives the same results as in Example 4 but with the explicit
estimation of three means and an intercept. The number of degrees of freedom is again
0, but the calculation of degrees of freedom goes a little differently. Sample means are
required for this analysis; therefore, the number of distinct sample moments includes
the sample means as well as the sample variances and covariances. There are four
sample means, four sample variances, and six sample covariances, for a total of 14
sample moments. As for the parameters to be estimated, there are three regression
weights and an intercept. Also, the three predictors have among them three means,
three variances, and three covariances. Finally, there is one error variance, for a total of
14 parameters to be estimated.
value
knowledge
performance
satisfaction
0,
error
1
Example 14
Job Performance of Farm Managers
Regression with an explicit intercept
(Model Specification)