Contrasts
Stata can now perform contrasts involving categorical variables and their
interactions after almost any estimation command. The new contrast
command provides a set of contrast operators that make it easy to specify
named contrasts such as reference-level contrasts, adjacent contrasts,
Helmert contrasts, and orthogonal polynomial contrasts. You can also
specify your own custom contrasts. contrast can perform joint tests
of these contrasts and can produce ANOVA-style tests of main effects,
interaction effects, simple effects, and nested effects.
We can use contrasts to answer questions about the way a categorical
variable relates to the response. If we fit the model
regress y i.agegroup
we could use reverse adjacent contrasts, which are specified with the
ar. operator, to test whether any age group could be combined with
the previous age group.
We could test whether there is a linear, quadratic, cubic, or even quartic
trend using orthogonal polynomial contrasts, which are specified with the
p. operator.
If we fit a two-way model
regress y agegroup##sex
we can test for main effects and interaction effects.
In this case, we could have obtained these tests from anova.
However, contrast can perform tests of main and interaction effects
after other types of models.
We can test for a difference in the estimated cell means for men and women
within each age group.
The margins
command now works with contrast operators as well so that we can obtain
contrasts of any margins that can be specified with this command, such as
contrasts of the marginal predicted probabilities after logistic regression.
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New in Stata 12
for more about what was added in Stata Release 12.
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