Hi Listers,
I am estimating a conditional logit model for a choice experiment where each individual is asked to select their preferred treatment between two alternatives. Each individual is presented with 10 choice sets (with two alternatives in each set). Alternatives are labelled A and B and have meaning because of the associated attributes.
The alternative specific variables are: adverse_events, disability_dummy, frequency_2, frequency_3, cost
I also have individual specific variables: age, sex, education, ethnicity, employment_status income
Previously I was advised that, to estimate the effect of case-specific variables on choice made, I should use interaction terms. However, interacting all the case-specific variables with all alternative-specific variables would generate too many variables.
So I have three questions:
a) Is there any way I could model the effect of case-specific variables without having to use a too many interaction terms?
b) If I want to account for the fact that each set of 10 choicesets was responded by one individual with the same case-specific variables, whats the best way to do so? My -clogit- command below takes account care of the fact that the alternatives belong to the same choice set but not that each set of 10 choice sets are responded by the same individual.
clogit choice adverse_events disability_dummy frequency_2 frequency_3 cost, group(choiceset)
c) If I use the above model, are case-specific variables assumed to be random or are they part of the intercept?
I would appreciate any help with this.
Thank you,
Shehzad
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