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Example
13
Estimating and Testing Hypotheses
about Means
Introduction
This example demonstrates how to estimate means and how to test hypotheses about
means. In large samples, the method demonstrated is equivalent to multivariate
analysis of variance.
Means and Intercept Modeling
Amos and similar programs are usually used to estimate variances, covariances, and
regression weights, and to test hypotheses about those parameters. Means and
intercepts are not usually estimated, and hypotheses about means and intercepts are
not usually tested. At least in part, means and intercepts have been left out of structural
equation modeling because of the relative difficulty of specifying models that include
those parameters.
Amos, however, was designed to make means and intercept modeling easy. The
present example is the first of several showing how to estimate means and intercepts
and test hypotheses about them. In this example, the model parameters consist only
of variances, covariances, and means. Later examples introduce regression weights
and intercepts in regression equations.