st: dirifit

[Viktor Slavtchev <viktor.slavtchev@uni-jena.de>]

Dear Nick,
first of all thank you very much for your kind response.

Nick Cox wrote:
> First question last. -dirifit- tries, among other things, to ignore
> observations in 
> which any response is 0 or 1.
> Viktor Slavtchev wrote:
> I want to explain the share of time that individuals spent on five
> distinct
> alternatives (y1 - y5). Hence y1+y2+y3+y4+y5=1.
> Therefore I run:
> dirifit y1-y5, mu(x1 x2)
> It works, however, for only 60 cases out of more than 500. That is, the
> estimation is done for 60 cases.
> Could it be that the -float- character of the dependent variable causes
> that
> problem? I am just wondering whether the possibility exists that the sum
> of y
> (=y1+y2+y3+y4+y5) becomes slightly lower or slightly larger than one
> when the
> dependent is -float-.
> -dirifit- can be estimated only if the sum is one.
> Is there a possibility to transform the variables in the way that 0.2534
> is
> exactly 0.2534 and not 0.253(3)9 or 0.2534(0)1?
Indeed, I do have a lot of cases where individuals spend some time on a 
particular activity, while do not consider other possibilities at all.
Hence, there are a lot of cases where at least one of the y's is 0 as 
well as cases where only one of the y's is 1. If I've got you correctly, 
-dirifit- ignores such cases.
This issue is actually stated in the help for -dirifit-:
"Note that cases will be ignored if the one or more of the dependent 
variables has a value less than or equal to zero or more than or equal 
to one or if the dependent variables don't add up to one."
So I really apologise for my ignorance.
Indeed, in only 60 cases (of 391) none of the y's is 0 or 1:

. count if y1!=0 & y2!=0 & y3!=0 & y4!=0 & y5!=0
60

Exactly these have been used for estimation:

. dirifit y1 - y5
<output skipped>

. gen dum1=1 if e(sample)
(331 missing values generated)

. gen dum2=1 if y1!=0 & y2!=0 & y3!=0 & y4!=0 & y5!=0
(331 missing values generated)

. gen diff=dum1-dum2
(331 missing values generated)

. tab diff

      diff |      Freq.     Percent        Cum.
------------+-----------------------------------
         0 |         60      100.00      100.00
------------+-----------------------------------
     Total |         60      100.00


*So the question would be, how to proceed when at least one of the 
responses is allowed to be 0, but the model is not really a model of 
competing alternatives (-mlogit-)?
Kind regards
Viktor

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