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:

  1. One of the levels of the interaction of EDU*STA is marginally significant.
  2. Only one of the levels of the interaction of POV*STA is marginally significant.

My questions are:

  1. How do you decipher a categorical-by-categorical interaction when only one level of the interaction is marginally significant?
  2. Would it be appropriate to calculate the adjusted odds, as a way to interpret the interaction?
  3. If 95% CI do not include 0 but the CI overlap, does it means that the results are not statistically significant?
  4. How do you visualize these interactions?

Thank you


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