The name is absent

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estimates the model:

y = a' +c' wgt                                     (continuous wgt effect)

+⅛ IaXwgt-2 + d''> IaXwgt-3 + d'₄ IaXwgt-4 (agegrp*wgt interactions)
+u'

The predicted values of y are

agegrp*wgt model        agegrp∣wgt model

That is, typing

. xi: regress y i.agegr*wgt

is equivalent t typing:

. xi: regress y i.agegr i.agegrIwgt

Also note that in either case, it is not necessary to specify separately the continuous variable wgt; it is included automatically.

Using ci: Interpreting output

. xi: regress mpg i.rep78

i.rep78               Irep78.1-5 (naturally coded; Irep78.1 omitted)

(output from regress appears)

Interpretation: i.rep78 expanded to the dummies Irep78.1, Irep78-2, ..., Irep78-5. The numbers on the end are “natural”
in the sense that Irep78_l corresponds to rep78 = 1, Irep78~2 to rep78 = 2, and so on. Finally, the dummy for rep78 = 1
was mitted.

. xi: regress mpg i.make

i.make                Imake_-l-74 (Imake_-1 for make==AMC Concord omitted)

(output from regress appears)

Interpretation: i.make expanded to Imake_l, Imake_2, ..., Imake_74. The coding is not natural because make is a string
variable. Imake_l corresponds to one make, Imake~2 another, and so on. We can find out the coding by typing ‘describe’.
Imake_l for the AMC Concord was chosen to be omitted.

How xi names variables

The names xi assigns to the dummy variables it creates are of the form:

SsUbbg∣ouppdd

You may subsequently refer to the entire set of variables by typing ‘!stub*’. For example:

xi as a command rather than a command prefix

xi can be used as a command prefix or as a command by itself. In the latter form, xi merely creates the indicator and
interactin variables. Equivalent t typing,

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