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Updates to factor variables were introduced in Stata 11.

See the latest version of factor variables. See all of Stata's basic statistics features.

See the new features in Stata 18.


Factor variables

Stata now handles factor (categorical) variables elegantly. You can now prefix a variable with i. to specify indicators for each level (category) of the variable. You can put a # between two variables to create an interaction–indicators for each combination of the categories of the variables. You can put ## instead to specify a full factorial of the variables—main effects for each variable and an interaction. If you want to interact a continuous variable with a factor variable, just prefix the continuous variable with c.. You can specify up to eight-way interactions.

We run a linear regression of cholesterol level on a full factorial of age group and whether the person smokes along with a continuous body mass index (bmi) and its interaction with whether the person smokes.


We could have used parenthesis binding, to type the same model more briefly:

. regress cholesterol smoker##(agegrp c.bmi)

Base levels can be changed on the fly: i.agegrp uses the default base level of 1, whereas b3.agegrp makes 3 the base level.

The level indicator variables are not created in your dataset, saving lots of space.

Factor variables are integrated deeply into Stata’s processing of variable lists, providing a consistent way of interacting with both estimation and postestimation commands.

For a complete list of new general statistics features in Stata 11, click here.

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