Sorry to nudge again on this; since the question was sent over the weekend, I thought some potential respondents may have missed it.
Any help on this would be appreciated.
Thank you,
Shehzad
----- Original Message ----
> From: Shehzad Ali <[email protected]>
> To: Stata List <[email protected]>
> Sent: Saturday, August 1, 2009 1:10:19 AM
> Subject: st: Conditional logit - how to account for within-subject correlation
>
> 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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