Your reference to dummies threw me.
As I see it, your 8 categories are (say)
----- binary ----- decimal
fert man fanyahu
0 0 0 0
0 0 1 1
0 1 0 2
0 1 1 3
1 0 0 4
1 0 1 5
1 1 0 6
1 1 1 7
which you can thus construct as (e.g.)
4 * fert + 2 * man + fanyahu
Nick
[email protected]
Ronnie Babigumira
> Thanks Nick, sorry for the lack of clarity, measure choice is
> my response (dependent is the term Im more farmiliar with)
> variable (s). I do have a set of predictor (independent)
> variables which I did not include in my email.
>
> Yes I did consider logit models for individual responses. I
> also considered constructing a dependent variable indicating
> whether or not any one of the choices was made.
>
> However, I have been thinking about the mlogit. So you say 8
> possible choices, would that mean 1, 2, 3 for fert, man,
> fanyaju rspv and then 5/8 for the diffrent combinations of
> each. If so, doesnt isnt this a problem because the classes
> are not exactly independent in the sense that (say 5 if
> choices 2 and 3 were made on the plot)
[email protected]
> I am not clear whether you regard
> measure choice as a predictor or a response.
> And in any case I can imagine
> situations in which both views are reasonable.
> Soil erosion loss could depend on
> conservation measures, which choice of conservation
> measures might depend on many things.
>
> If it were the latter, I think it is up to you how you define
> a composite response. Nor is it clear to me that
> you need do that. If this were my problem
> I would look at
>
> (a) logit models for the individual responses
>
> and
>
> (b) a multinomial logit for the 8 possible choices of
> fert[iliser?]
> man[ure?]
> and fanyaju[???].
>
> If conservation measures are predictors, you would
> need to look not just at dummies but also at interactions.
Ronnie Babigumira
> > Something has been slowly eating away at me and at this point I have
> > decided to seek help from the list. I have plot level data on use of
> > soil conservation measures and would like to construct a "single"
> > dependent variable for each household for use in a
> multinomial logit.
> > The data look something like this
> >
> > hhd_id plnum fert man fanyaju
> > 1001 1 0 1 0
> > 1001 2 0 1 1
> > 1001 3 1 0 1
> > 1002 1 0 0 0
> > 1002 2 1 1 1
> > 1003 1 1 0 0
> >
> > Where
> > hhd_id: Household id
> > plnum: Plot number (a household may have more than one plot)
> > And fert, man and fanyaju are 3 possible soil conservation
> measures a
> > household may undertake (it is possible that more than one
> measure can
> > be applied to a plot)
> >
> > My question is how do I go about with constructing a single
> dependent
> > variable for use in a multinomial logit in this case (and
> > would this be
> > correct). I have considered the simplest case where I
> > construct a simple
> > dummy for each plot indicating whether or not a household
> > used at least
> > one of the measures however, I feel that it would be more
> > interesting if
> > I could say something on the determinants for the use of
> the different
> > measures
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