st: Interpreting interactions

[Amal Khanolkar <Amal.Khanolkar@ki.se>]

Hi,

I ran the following set of logistic regression models:

1. Crude:

xi: logit vent6h i.mom_race2 sexx if age_mom!=. & parity!=. & gestcalc!=. & cigs_befx!=. & gestdb!=. & gesthy!=. & MBMI!=. & ht_cm!=. & plural==1 & edu_mom!=. & marriedx!=., or

2.  Adjusted for confounders:

xi: logit vent6h i.mom_race2 i.edu_mom i.marriedx age_mom sexx age_mom i.parity gestcalc i.cigs_befx i.gestdb i.gesthy i.MBMI ht_cm if plural==1., or

3. With interactions:

xi: logit vent6h i.mom_race2*i.edu_mom i.mom_race2*i.marriedx sexx age_mom i.parity gestcalc i.cigs_befx i.gestdb i.gesthy i.MBMI ht_cm if plural==1., or


I see that the Odds ratios (for racial groups) do not really change between models 1 and 2 - i.e. additional adjustment for potential confounders do not seen to affect the odds of a particular ethnic group of being diagnosed with my outcome of interest.

However, I see that the OR for ethnic group 2 go from 1.23 (95% CI 1.00 to 1.48) in model 1 to 1.13 (0.92 to 1.37) in model 2 to 2.33 (1.46 to 3.72) in model 3.

Model 3 only has the interactions in it, otherwise it is the same as model 2. How does one interpret the OR's for i.mom_race2 in model 3? I get the usual set of OR's for mom_race2 in the beginning of the output, and the the interactions towards the bottom of the model. 

I assumed that the OR's in model 3 should be same as those in model 2 as I'm not additionally adjusting for anything new (ie it is the same as model 2 except for the interaction term).


Thanks,



Amal Khanolkar

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