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I have the following model:

logistic regression:

outcome ~ b1*age + b2*smoker + b3*age:smoker

smoker has two levels: non-smoker, smoker
age is a continuous variable

likelihood ratio test shows the interaction term is insignificant

How should I interpret b1?

interpret b1:

The effect of one unit change in age on outcome (log adds), controlling for effect of smoking status (keep smoking status constant).

another way to interpret b1:

The effect of one unit change in age on outcome for non-smoker (non-smoker is the base level, in this case, smoker==0)

I'm a little confused. There interpretation does not seems to be the same... Can anyone clarify me on this? Thanks a lot.

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  • $\begingroup$ stats.stackexchange.com/questions/380222/… $\endgroup$
    – Huy Pham
    Commented Dec 19, 2018 at 19:44
  • $\begingroup$ The second interpretation is correct. When the interaction between age and gender exists, there is no common effect of age, so the first interpretation is meaningless. $\endgroup$
    – user158565
    Commented Dec 19, 2018 at 21:45
  • $\begingroup$ I tested the interaction. The interaction is insignificant. So how should I interpret that? which one is right. @user158565 $\endgroup$
    – zesla
    Commented Dec 19, 2018 at 22:10
  • $\begingroup$ It depends on the model. Even the interaction is not significant, but you insist to keep it in the model, then the second interpretation is correct. If you refit the model by excluding the insignificant interaction, then first explanation is correct. $\endgroup$
    – user158565
    Commented Dec 19, 2018 at 22:27
  • 2
    $\begingroup$ Your question implicitly changes the model halfway through. Either your model is the one you gave or it is the one without the interaction. It cannot simultaneously be both. Which one do you want to interpret? Answers to both have been given elsewhere on this site. $\endgroup$
    – whuber ♦
    Commented Dec 19, 2018 at 22:39

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