I've always used syntax to create dummy variables and it works the same
in PSPP and SPSS. 

If you had a categorical variable X with *three* values 0/1/2 you would
create *two* dummy coded variables like this:

recode x (0=1) (1=0) (2=0) (ELSE=SYSMIS) into x_dum1.
recode x (0=0) (1=1) (2=0) (ELSE=SYSMIS) into x_dum2.
execute.

This creates two dummy variables called x_dum1 and x_dum2 and they
encode the effect for category 0 and 1 (respectively) vs. category 2 as
a reference.  If you wanted to use, say, group 1 as the reference, then
you make sure that 1 is encoded as zero for both dummy variables:

recode x (0=1) (1=0) (2=0) (ELSE=SYSMIS) into x_dum1.
recode x (0=0) (1=0) (2=1) (ELSE=SYSMIS) into x_dum2.
execute.

Sometimes to give myself more flexibility, I create dummy codes for all
three values and only pick two in any analysis.  This forces the
category of the left out dummy variable to be the reference:

recode x (0=1) (1=0) (2=0) (ELSE=SYSMIS) into x_dum0.
recode x (0=0) (1=1) (2=0) (ELSE=SYSMIS) into x_dum1.
recode x (0=0) (1=0) (2=1) (ELSE=SYSMIS) into x_dum2.
execute.

For example, if you enter x_dum0 and x_dum2 then category 1 is the
reference.  If you forget and enter all three dummy variables the
regression should fail because the data matrix lacks full rank.

-Alan


On 9/29/2016 9:58 AM, Jack Drew wrote:
> Thanks for the speedy response, Alan.
>
> To be clear: if memory serves SPSS lets you specify the reference
> value for a categorical variable.  So for a variable with 0/1/2
> values, you can specify '0' as the reference category.
>
> However, if I understand you correctly, the method for PSPP is to
> create a dummy variable (0/1) for each of the 0/1/2 values and then
> exclude the dummy variable for 0 as the reference group.  You can run
> additional models and swap out the remaining variables to change
> reference group.
>
> Jack

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