I am working with multiply imputed data and I have run a logistic regression model with 6 predictors (3 dichotomous and 3 categorical) and their interaction terms, controlling for a number relevant covariates in SAS.
The predictor variables are as follow:
- CVD (0 = No; 1 =Yes)
- HCA (0 = Low; 1= High)
- EDU (1=High School Dropout; 2=Graduated High School; 3=Some College; 4=Graduated College)
- POV (1=Low; 2=Medium; 3=High)
- LAN (1=Spanish; 2=English)
- STA (0=Old, 1=New, 2=None)
My outcome variable is diabetes medication use and is coded as 0 = no use and 1 = current use
I found that for the following:
- One of the levels of the interaction of EDU*STA is marginally significant.
- Only one of the levels of the interaction of POV*STA is marginally significant.
My questions are:
- How do you decipher a categorical-by-categorical interaction when only one level of the interaction is marginally significant?
- Would it be appropriate to calculate the adjusted odds, as a way to interpret the interaction?
- If 95% CI do not include 0 but the CI overlap, does it means that the results are not statistically significant?
- How do you visualize these interactions?