Re: interaction terms in regression model


pbrewster@xxxxxxxxxxx wrote:
If I have an interaction term in my regression model that is
statistically significant, but one or both of the original attributes
are not statistically significant, should I remove original attributes
that are not statistically significant from the model?

For example, I create an interaction C=A*B. In my regression model, C
is statistically significant but A and B are not. Should I leave them
in the model or remove them?

Everyone is giving very statistical answers (which I guess makes sense
for a stats newsgroup :).

My question is can you explain this interaction clinically? Is it
plausible? Can you avoid overfit? If not, you may have grounds for
droping the individual predictor terms and the interaction term.

Marc

.

Relevant Pages

  • Re: interaction terms in regression model
    ... Can you avoid overfit? ... droping the individual predictor terms and the interaction term. ... are not statistically significant, ...
    (sci.stat.edu)
  • Re: interaction terms in regression model
    ... attributes are not statistically significant, ... interaction term) has the interpretation that there is no effect ... look at the shapes of the functions being allowed into the prediction. ... individual predictor terms and the interaction term. ...
    (sci.stat.edu)