Alright I guess its best to begin by stating my variables. All of them are dichotomized categorical variables. I have 5 exposure variables(plus two demographics-sex and race) so a total of 7, on 1 outcome variable. I've ran through the typical stuff: I ran my proc corr, chisq, proc surveylogistic of each exposure independently on the outcome, I then ran proc surveylogistic with the entire model(all five exposures plus demographics on my outcome) and my coding for the surveylogistic with the entire model looks like:
Proc surveylogsitic;
strata STRATUM;
cluster PSU;
weight WEIGHT;
class (I list all of my exposure variables) /param=reference;
model: outcome= expsoure variables;
run;
But my problem isnt getting the odds ratios of the entire model its that I then checked for interaction effects, and found interaction effects exist among two demographic variables: sex and race. So normally to tease out the interaction odds ratios, one would use an " if then" statement correct? but I was told that since I am using a weighted dataset, one simply cannot do this and must use a flag variable to create dummy variables or use LSMestimates to get odds ratios of each exposure variable on the outcome variable stratified by sex, and then stratified by race. But I really am just barely getting the hang of coding in SAS for all the other tests and not sure how one creates dummy variables, let alone how to do it with a weighted dataset. So really my question is, now that I have discovered an interaction, how do I re-run my logistic regression so that I get an odds ratio of each of my exposure variables on my outcome variable for females, for males, for whites, for african americans, for hispanics, etc...
