I developed the ordinal model where the outcome (high, middle low) is predicted from variables socioeconomic status (low, middle or high), child/adult relationship (family type A, B or C), and some other variables.
I fitted the interaction between the status of the family and the adult-child relationship, but I am not sure how to interpret the effects of this interaction.
If there were no interaction I would say that the middle family status increases the odds of the outcome by 50% and the high by 130% and family_B has no significant effect, while family_C increases the odds by 24%.
I think that in the presence of interaction, the above odds are only interpretable as above if the other variable is at the reference level and at the other levels of both variables there is the effect modification.
But considering that the effects for one family_B level and many levels of interaction are not significant, I do not know by how much, and if at all the effects are modified.
- In the case of the high socioeconomic status and family_C would the actual effect be: exp(beta(high) + beta(family_C) + beta(high*family_C)
exp( log(2.32) + log(1.24) + log(0.98))
or, should I ignore beta(high*family_C) as it is not significant?
- In the case of the middle socioeconomic status and family_B would the actual effect be: exp(beta(middle) + beta(family_B) + beta(middle*family_B),
but in this case, both family_B and middle*family_B are not significant. Are they included or are they both ignored?
I want to write two sentences: The odds of the outcome high vs middle or low when growing up with middle SES and family_B are XX higher/ lower than of growing up in the family with low SES and family_A.
The odds of the outcome high vs middle or low when growing up with high SES and family_C are XXX higher/lower than of growing up in a family with low SES and family_A.
How to calculate what the XX and XXX are equal to?
The problem of interaction and not significant terms have been discussed many times, but I have not found the answer where there was an explanation on how to provide the actual size of modification when dealing with not significant variables.
Thanks for any help
The interaction between high SES and family C is insignificant but pairwise comparisons of high ses family_c to high ses family_a and high ses family_c to middle ses family_a and high ses family_c to low ses family_a are all significant. Does it mean that there is an interaction on some levels but not the other? But why is the interaction in main output in the model not significant? Are these pairwise effect spurious? Additionally when comering the model with interaction to one without, adjusted R2 are the same, but Wald test is significant. I expected the interaction to be significant based on the previous evidence from literature review, and I would not want to misinterpret the results I got.