In the program below, I want to check the interaction between gender*race and gender*income.
In the model, I have 4 individual race variables and 3 individual income variables.
I also have a another form of “RACE” and “Income” variables, with 5 and 4 different levels, such as 1= white, 2=black, 3= hispanic, 4 =asian and 5=others and Income as 1= first quartile 2-= second quartile, 3= 3rd quartile and 4= 4th quartile.
I created the below yellow highlighted dichotomous variables from the above nominal variables to use them in the model;
Such as for race;
black , Hispanic, asian, otherraces, and Caucasian is a reference (these are dummy coded variables) from main variable “RACE”
for income;
secquart, thirquart, fourquart, (First quartile is the reference, again dummy coded from main variable “INCOME”
So which form of race and income variables should I use in interaction? I came up with following 2 types of models with interaction terms, please have a look at them and guide me as to which one of these is the correct one?
proc logistic data=library.nismicathcabg1 descending;
model died= age gender black hispanic asian otherraces secquart thirquart fourquart bldloss chf chrnlung coag depress drug hypothy liver lymph gender*black gender*hispanic gender*asian gender*otherraces gender*secquart gender*thirquart gender*fourquart;
title 'Logi Reg in-hosp mortality vs gender in MI patients with race + income';
run;
quit;
OR
This includes the nominal RACE AND INCOME variable in the interaction terms.
proc logistic data=library.nismicathcabg1 descending;
model died= age gender black hispanic asian otherraces secquart thirquart fourquart bldloss chf chrnlung coag depress drug hypothy liver lymph gender*race gender*income;
title 'Logi Reg in-hosp mortality vs gender in MI patients with race + income';
run;
quit;
or
proc logistic data=library.nismicathcabg1 descending;
class gender race (ref= first) income (ref=first) /param=ref;
model died= age gender race income bldloss chf chrnlung coag depress drug hypothy liver lymph gender*race1 gender*income;
title 'Logi Reg in-hosp mortality vs gender in MI patients with race + income';
run;
quit;
which one of these is right?
Appreciate your suggestions. i have never worked with 'interactions' before.
After I run these models, I get different numbers and the output doesnot show "ODDS estimate for gender, and the variables that are used in interaction terms. I am not sure if i am doing it right, as it is strange not to get the ODDS estimate for only these variables.
