Interaction Term in nonlinear model

[connie]

Dear Experts,

I have a choice experiment data including the population of cancer and non-cancer. I want to compare whether preferences for attributes differ between cancer and non-cancer groups. My first thought is to generate interaction terms between cancer indicator and attributes. According to Greene, W.H. (2010) and Ai, C. and Norton, E. (2003) , it seems interaction terms in non-linear model may not provide correct information. However, I also noticed some papers created interaction terms between social characteristics (such as age) and attributes. I am confused with this paradox.
My questions are: 1. may I analyze the data as a whole and generate interaction terms between cancer indicator and attributes as a way to compare preferences between two groups ? 2. if not, do I need to run the model on two groups separately? Any other suggestions?

Many thanks,

Connie

[Michiel Bliemer]

HI Connie,

I would create an interaction term between a dummy coded cancer variable and attributes, exactly as you propose. I am not sure why this would lead to wrong results as this has been the way people have done it for a long time. I am not aware of issues mentioned by Greene or Ai & Norton, what do they say specifically?

Michiel

[connie]

Thanks for the confirmation, Michiel. Ai, C. and Norton, E. (2003) said the sign of interaction term and its marginal effect are not easy to calculate. May be I got the wrong understanding.

[Michiel Bliemer]

I am not sure what article you are referring to, but I do not see why computing interaction terms and their marginal effects would be an issue, so I would suggest that you add interaction terms as you suggested as this is commonly done.

Michiel