Freezing variables in regression

[Nimish_Vaddiparti]

Hi,

I'm using proc regression and i want to freeze a few variables. In other words, i dont want a few variables to get dropped. I'm trying to build a code, which can be used going forward. And where the user does not need to keep manually force including these variables.

Any ideas how i can take this forward?

Regards,

Nimish

[stat_sas · Accepted solution]

Hi,

Put INCLUDE=n  in model statement, that forces the first n independent variables listed in the MODEL statement to be included in all models.

Thanks,

Naeem

[Nimish_Vaddiparti]

Hi,

Can you help with the statement? As in where should i add the include option?

Cheers,

Nimish

[stat_sas]

Hi,

proc reg data=have;

model  y=x1 x2 x3 x4/include=2 selection=forward;

quit;

First two variables x1 and x2 will be included in the model.

Thanks,

Naeem

[Nimish_Vaddiparti]

Hi Naeem,

I'm looking to use the regression output to build a new model. Lets say i have 10 variables in my initial model. And out of the 10, 2 have a high p -value. Now, I want to rerun my regression equation, after excluding these two variables, without having to manually write the code. Is this possible? If yes, can you suggest the best way forward.

Regards,

Nimish

[stat_sas]

Hi,

Is there any cut off value to decide whether p-value high or not?

Thanks,

Naeem

[lvm]

I don't like the idea of automating this based on fixed p values. Model building should involve judgements and interpretation. All the stepwise procedures are VERY dangerous to start with, unless derived models are tested on independent data (at a minimum). p values can be very misleading in stepwise procedures. I highly recommend that you check out the GLMSELECT procedure for better ways of selecting predictor variables. The SAS Global Forum has some nice articles on use of this procedure.