[R] reduced set of alternatives in package mlogit

[John Kane]

To back up Ber's please have a look at
http://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example and/or http://adv-r.had.co.nz/Reproducibility.html

John Kane
Kingston ON Canada


> -----Original Message-----
> From: jose.ferraro at logiteng.com
> Sent: Wed, 13 Apr 2016 17:18:35 +0000
> To: cdesjard at umn.edu
> Subject: Re: [R] reduced set of alternatives in package mlogit
> 
> 
> 
> code? example data?  We can only guess based on your vague post.
> 
> "PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code."
> 
> Moreover, this sounds like a statistical question, not a question about R
> programming, and so might be more appropriate for a statistical list like
> stats.stackexchange.com<http://stats.stackexchange.com>  .
> 
> Cheers,
> Bert
> 
> 
> Bert Gunter
> 
> 
> 
> Sorry if I was not clear enough, but  there is hardly any code to show.
> The problem is that a parameter or function is lacking (or , mostly
> likely, I can't find it), so in some sense the problem itself is that
> there is no code to show.
> 
> In what follows choice situations , alternatives, wide, and variables
> have the same meaning that they have on the mlogit documentation. All
> variables are alternative specific.
> 
> 1)I want to estimate a multinomial Logit  using the mlogit package
> 
> 2)I have a dataset, made of choice situations
> 
> 3)There is a set of alternatives
> 
> 4)in some choice situations, not all alternatives were available, but
> only a subset of them. So there are no variables for the unavailable
> alternatives and the chosen alternative evidently  belongs to the set of
> available ones.
> 
> 5)I use mlogit.data to prepare the dataset from a "wide" dataframe .
> There is no option to have only a subset of alternatives and the
> resulting object will have them all , that is, there will be a line for
> every alternative and every choice situation, even if in reality some of
> them were not available. The variables of these alternatives did not
> exist, so must be filled with 0s or any other made up value
> 
> 6) If ones estimate a model from this data it will be wrong
> 
> 7) It is possible to get an "almost right" model by using a dummy
> variable marking which alternatives are unavailable, for as it is only
> used in alternatives that are never chosen, its coefficient will get
> negative with big absolute value, in practice giving almost 0%
> probability for them
> 
> 8)this is a workaround because it obligates the model to estimate a
> number that should be -infinity and this is known in advance, so it's
> ugly and difficult to know what the numeric consequences are as the
> coefficient can never converge. In fact, I don't use it the way I
> described for these reasons, preferring a more complex but almost
> equivalent formulation. The important point is that I want a clean
> solution, not a workaround
> 
> 9)I demand simply if mlogit package has such functionality
> 
> 
> 
> 
> 
> Hi,
> I meant that in some choice situations there are some alternatives
> missing, but the available alternatives are known to everybody(both the
> one that made the choice as well as to who collected the data).
> For future reference, I would like to post here that I found the answer.
> Apparently it is not possible if one uses mlogit.data  with shape =
> “wide”, but it is if one uses it with shape = “long” .
> So basically one can create an alternative specific variable with
> availability (let’s call it is_avaliable) and use mlogit.data  normally
> that is :
> all_avaliable <- mlogit.data(df , shape = “wide” , …)
> then one can subset it
> real_avaliability <-  all_avaliable[all_avaliable$is_avaliable ,]
> and resend it through mlogit.data with format long
> mlogit.data(real_avaliability , shape = "long" , alt.var = "alt" ,
> chid.var = "chid", …)
> please observe that alt and chid will have been created by the first call
> to mlogit.data
> 
> 	[[alternative HTML version deleted]]
> 
> ______________________________________________
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> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.

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