Re: PSPP linear regression (reference category).

[Alan Mead]

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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