Since this is an assignment there are probably some other things that effect the answer. You have 7 variables and 2 way interactions alone are a lot.
You can specify interaction terms in the model statement as:
model mort_10yr(ref='0') = age | sex | race | educ @2 / <list of options>;
@the | pipe symbol tells SAS to consider interactions between the variables and then the @2 tells SAS to limit it to interaction level between 2 variables.
@3 would test 3-way interactions such as age*sex*race.
You can explicitly list interactions such as:
age*sex educ*race
This is covered in the documentation here:
http://documentation.sas.com/?docsetId=casecon&docsetTarget=viyaets_introcom_sect021.htm&docsetVersi...
You can include all variables in the initial model, if you have enough observations to allow for that. You're possibly testing 7 + 21 two way combinations and categorical variables will increase the numbers. A good rule of thumb is 25 obs per predictor so you would need at minimum 28*25 = 700 obs to start off with.
I'm going to move this to the Stats forum so the stats people can comment.
@iressa131 wrote:
Hello,
I am attempting to build a model with 7 predictors and a binary outcome. I can only use stepwise selection for my assignment. Here is what I currently have in SAS university. Now i know i need to account for possible interactions but how would I do this? Do I include all possible interaction terms in THIS model or do I code for additional models, each one containing a different set of variables/interactions of interest? Thanks in advance for any help!
proc logistic data=fp;
class race(ref='White') Sex(ref='F')/param=reference;
model mort_10yr(ref='0') = age sex race educ income_pov_indx log_cotinine log_tungsten FP FI
/selection=stepwise slentry=0.2 slstay=0.15 details lackfit;
run;
